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  • 1. Adams, Hieab H. H.
    et al.
    Hibar, Derrek P.
    Chouraki, Vincent
    Stein, Jason L.
    Nyquist, Paul A.
    Renteria, Miguel E.
    Trompet, Stella
    Arias-Vasquez, Alejandro
    Seshadri, Sudha
    Desrivieres, Sylvane
    Beecham, Ashley H.
    Jahanshad, Neda
    Wittfeld, Katharine
    Van der Lee, Sven J.
    Abramovic, Lucija
    Alhusaini, Saud
    Amin, Najaf
    Andersson, Micael
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Arfanakis, Konstantinos
    Aribisala, Benjamin S.
    Armstrong, Nicola J.
    Athanasiu, Lavinia
    Axelsson, Tomas
    Beiser, Alexa
    Bernard, Manon
    Bis, Joshua C.
    Blanken, Laura M. E.
    Blanton, Susan H.
    Bohlken, Marc M.
    Boks, Marco P.
    Bralten, Janita
    Brickman, Adam M.
    Carmichael, Owen
    Chakravarty, M. Mallar
    Chauhan, Ganesh
    Chen, Qiang
    Ching, Christopher R. K.
    Cuellar-Partida, Gabriel
    Den Braber, Anouk
    Doan, Nhat Trung
    Ehrlich, Stefan
    Filippi, Irina
    Ge, Tian
    Giddaluru, Sudheer
    Goldman, Aaron L.
    Gottesman, Rebecca F.
    Greven, Corina U.
    Grimm, Oliver
    Griswold, Michael E.
    Guadalupe, Tulio
    Hass, Johanna
    Haukvik, Unn K.
    Hilal, Saima
    Hofer, Edith
    Hoehn, David
    Holmes, Avram J.
    Hoogman, Martine
    Janowitz, Deborah
    Jia, Tianye
    Kasperaviciute, Dalia
    Kim, Sungeun
    Klein, Marieke
    Kraemer, Bernd
    Lee, Phil H.
    Liao, Jiemin
    Liewald, David C. M.
    Lopez, Lorna M.
    Luciano, Michelle
    Macare, Christine
    Marquand, Andre
    Matarin, Mar
    Mather, Karen A.
    Mattheisen, Manuel
    Mazoyer, Bernard
    Mckay, David R.
    McWhirter, Rebekah
    Milaneschi, Yuri
    Mirza-Schreiber, Nazanin
    Muetzel, Ryan L.
    Maniega, Susana Munoz
    Nho, Kwangsik
    Nugent, Allison C.
    Loohuis, Loes M. Olde
    Oosterlaan, Jaap
    Papmeyer, Martina
    Pappa, Irene
    Pirpamer, Lukas
    Pudas, Sara
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Puetz, Benno
    Rajan, Kumar B.
    Ramasamy, Adaikalavan
    Richards, Jennifer S.
    Risacher, Shannon L.
    Roiz-Santianez, Roberto
    Rommelse, Nanda
    Rose, Emma J.
    Royle, Natalie A.
    Rundek, Tatjana
    Saemann, Philipp G.
    Satizabal, Claudia L.
    Schmaal, Lianne
    Schork, Andrew J.
    Shen, Li
    Shin, Jean
    Shumskaya, Elena
    Smith, Albert V.
    Sprooten, Emma
    Strike, Lachlan T.
    Teumer, Alexander
    Thomson, Russell
    Tordesillas-Gutierrez, Diana
    Toro, Roberto
    Trabzuni, Daniah
    Vaidya, Dhananjay
    Van der Grond, Jeroen
    Van der Meer, Dennis
    Van Donkelaar, Marjolein M. J.
    Van Eijk, Kristel R.
    Van Erp, Theo G. M.
    Van Rooij, Daan
    Walton, Esther
    Westlye, Lars T.
    Whelan, Christopher D.
    Windham, Beverly G.
    Winkler, Anderson M.
    Woldehawariat, Girma
    Wolf, Christiane
    Wolfers, Thomas
    Xu, Bing
    Yanek, Lisa R.
    Yang, Jingyun
    Zijdenbos, Alex
    Zwiers, Marcel P.
    Agartz, Ingrid
    Aggarwal, Neelum T.
    Almasy, Laura
    Ames, David
    Amouyel, Philippe
    Andreassen, Ole A.
    Arepalli, Sampath
    Assareh, Amelia A.
    Barral, Sandra
    Bastin, Mark E.
    Becker, Diane M.
    Becker, James T.
    Bennett, David A.
    Blangero, John
    van Bokhoven, Hans
    Boomsma, Dorret I.
    Brodaty, Henry
    Brouwer, Rachel M.
    Brunner, Han G.
    Buckner, Randy L.
    Buitelaar, Jan K.
    Bulayeva, Kazima B.
    Cahn, Wiepke
    Calhoun, Vince D.
    Cannon, Dara M.
    Cavalleri, Gianpiero L.
    Chen, Christopher
    Cheng, Ching -Yu
    Cichon, Sven
    Cookson, Mark R.
    Corvin, Aiden
    Crespo-Facorro, Benedicto
    Curran, Joanne E.
    Czisch, Michael
    Dale, Anders M.
    Davies, Gareth E.
    De Geus, Eco J. C.
    De Jager, Philip L.
    de Zubicaray, Greig I.
    Delanty, Norman
    Depondt, Chantal
    DeStefano, Anita L.
    Dillman, Allissa
    Djurovic, Srdjan
    Donohoe, Gary
    Drevets, Wayne C.
    Duggirala, Ravi
    Dyer, Thomas D.
    Erk, Susanne
    Espeseth, Thomas
    Evans, Denis A.
    Fedko, Iryna
    Fernandez, Guillen
    Ferrucci, Luigi
    Fisher, Simon E.
    Fleischman, Debra A.
    Ford, Ian
    Foroud, Tatiana M.
    Fox, Peter T.
    Francks, Clyde
    Fukunaga, Masaki
    Gibbs, J. Raphael
    Glahn, David C.
    Gollub, Randy L.
    Goring, Harald H. H.
    Grabe, Hans J.
    Green, Robert C.
    Gruber, Oliver
    Gudnason, Vilmundur
    Guelfi, Sebastian
    Hansell, Narelle K.
    Hardy, John
    Hartman, Catharina A.
    Hashimoto, Ryota
    Hegenscheid, Katrin
    Heinz, Andreas
    Le Hellard, Stephanie
    Hernandez, Dena G.
    Heslenfeld, Dirk J.
    Ho, Beng-Choon
    Hoekstra, Pieter J.
    Hoffmann, Wolfgang
    Hofman, Albert
    Holsboer, Florian
    Homuth, Georg
    Hosten, Norbert
    Hottenga, Jouke-Jan
    Pol, Hilleke E. Hulshoff
    Ikeda, Masashi
    Ikram, M. Kamran
    Jack, Clifford R., Jr.
    Jenldnson, Mark
    Johnson, Robert
    Jonsson, Erik G.
    Jukema, J. Wouter
    Kahn, Rene S.
    Kanai, Ryota
    Kloszewska, Iwona
    Knopman, David S.
    Kochunov, Peter
    Kwok, John B.
    Lawrie, Stephen M.
    Lemaitre, Herve
    Liu, Xinmin
    Longo, Dan L.
    Longstreth, W. T., Jr.
    Lopez, Oscar L.
    Lovestone, Simon
    Martinez, Oliver
    Martinot, Jean-Luc
    Mattay, Venkata S.
    McDonald, Colm
    McIntosh, Andrew M.
    McMahon, Katie L.
    McMahon, Francis J.
    Mecocci, Patrizia
    Melle, Ingrid
    Meyer-Lindenberg, Andreas
    Mohnke, Sebastian
    Montgomery, Grant W.
    Morris, Derek W.
    Mosley, Thomas H.
    Muhleisen, Thomas W.
    Mueller-Myhsok, Bertram
    Nalls, Michael A.
    Nauck, Matthias
    Nichols, Thomas E.
    Niessen, Wiro J.
    Noethen, Markus M.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Ohi, Kazutaka
    Olvera, Rene L.
    Ophoff, Roel A.
    Pandolfo, Massimo
    Paus, Tomas
    Pausova, Zdenka
    Penninx, Brenda W. J. H.
    Pike, G. Bruce
    Potkin, Steven G.
    Psaty, Bruce M.
    Reppermund, Simone
    Rietschel, Marcella
    Roffman, Joshua L.
    Romanczuk-Seiferth, Nina
    Rotter, Jerome I.
    Ryten, Mina
    Sacco, Ralph L.
    Sachdev, Perminder S.
    Saykin, Andrew J.
    Schmidt, Reinhold
    Schofield, Peter R.
    Sigurdsson, Sigurdur
    Simmons, Andy
    Singleton, Andrew
    Sisodiya, Sanjay M.
    Smith, Colin
    Smoller, Jordan W.
    Soininen, Hindu.
    Srikanth, Velandai
    Steen, Vidar M.
    Stott, David J.
    Sussmann, Jessika E.
    Thalamuthu, Anbupalam
    Tiemeier, Henning
    Toga, Arthur W.
    Traynor, Bryan J.
    Troncoso, Juan
    Turner, Jessica A.
    Tzourio, Christophe
    Uitterlinden, Andre G.
    Hernandez, Maria C. Valdes
    Van der Brug, Marcel
    Van der Lugt, Aad
    Van der Wee, Nic J. A.
    Van Duijn, Cornelia M.
    Van Haren, Neeltje E. M.
    Van't Ent, Dennis
    Van Tol, Marie Jose
    Vardarajan, Badri N.
    Veltman, Dick J.
    Vernooij, Meike W.
    Voelzke, Henry
    Walter, Henrik
    Wardlaw, Joanna M.
    Wassink, Thomas H.
    Weale, Michael E.
    Weinberger, Daniel R.
    Weiner, Michael W.
    Wen, Wei
    Westman, Eric
    White, Tonya
    Wong, Tien Y.
    Wright, Clinton B.
    Zielke, H. Ronald
    Zonderman, Alan B.
    Deary, Ian J.
    DeCarli, Charles
    Schmidt, Helena
    Martin, Nicholas G.
    De Craen, Anton J. M.
    Wright, Margaret J.
    Launer, Lenore J.
    Schumann, Gunter
    Fornage, Myriam
    Franke, Barbara
    Debette, Stephanie
    Medland, Sarah E.
    Ikram, M. Arfan
    Thompson, Paul M.
    Novel genetic loci underlying human intracranial volume identified through genome-wide association2016In: Nature Neuroscience, ISSN 1097-6256, E-ISSN 1546-1726, Vol. 19, no 12, p. 1569-1582Article in journal (Refereed)
    Abstract [en]

    Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (rho(genetic) = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (N-combined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.

  • 2.
    af Bjerkén, Sara
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences.
    Axelsson, Jan
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Flygare, Carolina
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Remes, Jussi
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Strandberg, Sara
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Eriksson, Linda
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences.
    Bäckström, David C.
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences.
    Jakobson Mo, Susanna
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Reliability and validity of visual analysis of [18F]FE-PE2I PET/CT in early Parkinsonian disease2023In: Nuclear medicine communications, ISSN 0143-3636, E-ISSN 1473-5628, Vol. 44, no 5, p. 397-406Article in journal (Refereed)
    Abstract [en]

    Objective: [18F]FE-PE2I (FE-PE2I) is a new radiotracer for dopamine transporter (DAT) imaging with PET. The aim of this study was to evaluate the visual interpretation of FE-PE2I images for the diagnosis of idiopathic Parkinsonian syndrome (IPS). The inter-rater variability, sensitivity, specificity, and diagnostic accuracy for visual interpretation of striatal FE-PE2I compared to [123I]FP-CIT (FP-CIT) single-photon emission computed tomography (SPECT) was evaluated.

    Methods: Thirty patients with newly onset parkinsonism and 32 healthy controls with both an FE-PE2I and FP-CIT were included in the study. Four patients had normal DAT imaging, of which three did not fulfil the IPS criteria at the clinical reassessment after 2 years. Six raters evaluated the DAT images blinded to the clinical diagnosis, interpreting the image as being ‘normal’ or ‘pathological’, and assessed the degree of DAT-reduction in the caudate and putamen. The inter-rater agreement was assessed with intra-class correlation and Cronbach’s α. For calculation of sensitivity and specificity, DAT images were defined as correctly classified if categorized as normal or pathological by ≥4/6 raters.

    Results: The overall agreement in visual evaluation of the FE-PE2I- and FP-CIT images was high for the IPS patients (α = 0.960 and 0.898, respectively), but lower in healthy controls (FE-PE2I: α = 0.693, FP-CIT: α = 0.657). Visual interpretation gave high sensitivity (both 0.96) but lower specificity (FE-PE2I: 0.86, FP-CIT: 0.63) with an accuracy of 90% for FE-PE2I and 77% for FP-CIT.

    Conclusion: Visual evaluation of FE-PE2I PET imaging demonstrates high reliability and diagnostic accuracy for IPS.

  • 3.
    af Bjerkén, Sara
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience.
    Stenmark Persson, Rasmus
    Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Barkander, Anna
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Karalija, Nina
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Pelegrina-Hidalgo, Noelia
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Gerhardt, Greg A
    Virel, Ana
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Strömberg, Ingrid
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Noradrenaline is crucial for the substantia nigra dopaminergic cell maintenance2019In: Neurochemistry International, ISSN 0197-0186, E-ISSN 1872-9754, Vol. 131, article id 104551Article in journal (Refereed)
    Abstract [en]

    In Parkinson's disease, degeneration of substantia nigra dopaminergic neurons is accompanied by damage on other neuronal systems. A severe denervation is for example seen in the locus coerulean noradrenergic system. Little is known about the relation between noradrenergic and dopaminergic degeneration, and the effects of noradrenergic denervation on the function of the dopaminergic neurons of substantia nigra are not fully understood. In this study, N-(2-chloroethyl)-N-ethyl-2-bromobenzylamine (DSP4) was injected in rats, whereafter behavior, striatal KCl-evoked dopamine and glutamate releases, and immunohistochemistry were monitored at 3 days, 3 months, and 6 months. Quantification of dopamine-beta-hydroxylase-immunoreactive nerve fiber density in the cortex revealed a tendency towards nerve fiber regeneration at 6 months. To sustain a stable noradrenergic denervation throughout the experimental timeline, the animals in the 6-month time point received an additional DSP4 injection (2 months after the first injection). Behavioral examinations utilizing rotarod revealed that DSP4 reduced the time spent on the rotarod at 3 but not at 6 months. KCl-evoked dopamine release was significantly increased at 3 days and 3 months, while the concentrations were normalized at 6 months. DSP4 treatment prolonged both time for onset and reuptake of dopamine release over time. The dopamine degeneration was confirmed by unbiased stereology, demonstrating significant loss of tyrosine hydroxylase-immunoreactive neurons in the substantia nigra. Furthermore, striatal glutamate release was decreased after DSP4. In regards of neuroinflammation, reactive microglia were found over the substantia nigra after DSP4 treatment. In conclusion, long-term noradrenergic denervation reduces the number of dopaminergic neurons in the substantia nigra and affects the functionality of the nigrostriatal system. Thus, locus coeruleus is important for maintenance of nigral dopaminergic neurons.

  • 4. Akram, Harith
    et al.
    Miller, Sarah
    Lagrata, Susie
    Hariz, Marwan
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Ashburner, John
    Behrens, Tim
    Matharu, Manjit
    Zrinzo, Ludvic
    Optimal deep brain stimulation site and target connectivity for chronic cluster headache2017In: Neurology, ISSN 0028-3878, E-ISSN 1526-632X, Vol. 89, no 20, p. 2083-2091Article in journal (Refereed)
    Abstract [en]

    Objective: To investigate the mechanism of action of deep brain stimulation for refractory chronic cluster headache and the optimal target within the ventral tegmental area. Methods: Seven patients with refractory chronic cluster headache underwent high spatial and angular resolution diffusion MRI preoperatively. MRI-guided and MRI-verified electrode implantation was performed unilaterally in 5 patients and bilaterally in 2. Volumes of tissue activation were generated around active lead contacts with a finite-element model. Twelve months after surgery, voxel-based morphometry was used to identify voxels associated with higher reduction in headache load. Probabilistic tractography was used to identify the brain connectivity of the activation volumes in responders, defined as patients with a reduction of >= 30% in headache load. Results: There was no surgical morbidity. Average follow-up was 34 +/- 14 months. Patients showed reductions of 76 +/- 33% in headache load, 46 +/- 41% in attack severity, 58 +/- 41% in headache frequency, and 51 +/- 46% in attack duration at the last follow-up. Six patients responded to treatment. Greatest reduction in headache load was associated with activation in an area cantered at 6 mm lateral, 2 mm posterior, and 1 mm inferior to the midcommissural point of the third ventricle. Average responders' activation volume lay on the trigeminohypothalamic tract, connecting the trigeminal system and other brainstem nuclei associated with nociception and pain modulation with the hypothalamus, and the prefrontal and mesial temporal areas. Conclusions: We identify the optimal stimulation site and structural connectivity of the deep brain stimulation target for cluster headache, explicating possible mechanisms of action and disease pathophysiology.

  • 5.
    Ambarki, Khalid
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Hallberg, Per
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Jóhannesson, Gauti
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Ophthalmology.
    Lindén, Christina
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Ophthalmology.
    Zarrinkoob, Laleh
    Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience.
    Wåhlin, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Birgander, Richard
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Malm, Jan
    Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience.
    Eklund, Anders
    Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience.
    Blood flow of ophthalmic artery in healthy individuals determined by phase-contrast magnetic resonance imaging2013In: Investigative Ophthalmology and Visual Science, ISSN 0146-0404, E-ISSN 1552-5783, Vol. 54, no 4, p. 2738-2745Article in journal (Refereed)
    Abstract [en]

    PURPOSE: Recent development of magnetic resonance imaging (MRI) offers new possibilities to assess ocular blood flow. This prospective study evaluates the feasibility of phase-contrast MRI (PCMRI) to measure flow rate in the ophthalmic artery (OA) and establish reference values in healthy young (HY) and elderly (HE) subjects.

    METHODS: Fifty HY subjects (28 females, 21-30 years of age) and 44 HE (23 females, 64-80 years of age) were scanned on a 3-Tesla MR system. The PCMRI sequence had a spatial resolution of 0.35 mm per pixel, with the measurement plan placed perpendicularly to the OA. Mean flow rate (Qmean), resistive index (RI), and arterial volume pulsatility of OA (ΔVmax) were measured from the flow rate curve. Accuracy of PCMRI measures was investigated using a vessel-phantom mimicking the diameter and the flow rate range of the human OA.

    RESULTS: Flow rate could be assessed in 97% of the OAs. Phantom investigations showed good agreement between the reference and PCMRI measurements with an error of <7%. No statistical difference was found in Qmean between HY and HE individuals (HY: mean ± SD = 10.37 ± 4.45 mL/min; HE: 10.81 ± 5.15 mL/min, P = 0.655). The mean of ΔVmax (HY: 18.70 ± 7.24 μL; HE: 26.27 ± 12.59 μL, P < 0.001) and RI (HY: 0.62 ± 0.08; HE: 0.67 ± 0.1, P = 0.012) were significantly different between HY and HE.

    CONCLUSIONS: This study demonstrated that the flow rate of OA can be quantified using PCMRI. There was an age difference in the pulsatility parameters; however, the mean flow rate appeared independent of age. The primary difference in flow curves between HE and HY was in the relaxation phase of the systolic peak.

  • 6.
    Ambarki, Khalid
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Science and Technology, Centre for Biomedical Engineering and Physics (CMTF).
    Petr, J.
    Wahlin, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Wirestam, R.
    Zarrinkoob, Laleh
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Malm, Jan
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Eklund, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Science and Technology, Centre for Biomedical Engineering and Physics (CMTF).
    Partial Volume Correction of Cerebral Perfusion Estimates Obtained by Arterial Spin Labeling2015In: 16th Nordic-Baltic Conference on Biomedical Engineering: 16. NBC & 10. MTD 2014 joint conferences. October 14-16, 2014, Gothenburg, Sweden, 2015, Vol. 48, p. 17-19Conference paper (Refereed)
    Abstract [en]

    Arterial Spin labeling (ASL) is a fully non-invasive MRI method capable to quantify cerebral perfusion. However, gray (GM) and white matter (WM) ASL perfusions are difficult to assess separately due to limited spatial resolution increasing the partial volume effects (PVE). In the present study, ASL PVE correction was implemented based on a regression algorithm in 22 healthy young men. PVE corrected perfusion of GM and WM were compared to previous studies. PVE-corrected GM perfusion was in agreement with literature values. In general, WM perfusion was higher despite the use of PVE correction.

  • 7.
    Ambarki, Khalid
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Science and Technology, Centre for Biomedical Engineering and Physics (CMTF).
    Wåhlin, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Zarrinkoob, Laleh
    Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience.
    Wirestam, R.
    Petr, J.
    Malm, Jan
    Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience.
    Eklund, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Science and Technology, Centre for Biomedical Engineering and Physics (CMTF). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Accuracy of Parenchymal Cerebral Blood Flow Measurements Using Pseudocontinuous Arterial Spin-labeling in Healthy Volunteers2015In: American Journal of Neuroradiology, ISSN 0195-6108, E-ISSN 1936-959X, Vol. 36, no 10, p. 1816-1821Article in journal (Refereed)
    Abstract [en]

    BACKGROUND AND PURPOSE: The arterial spin-labeling method for CBF assessment is widely available, but its accuracy is not fully established. We investigated the accuracy of a whole-brain arterial spin-labeling technique for assessing the mean parenchymal CBF and the effect of aging in healthy volunteers. Phase-contrast MR imaging was used as the reference method. MATERIALS AND METHODS: Ninety-two healthy volunteers were included: 49 young (age range, 20-30 years) and 43 elderly (age range, 65-80 years). Arterial spin-labeling parenchymal CBF values were averaged over the whole brain to quantify the mean pCBF(ASL) value. Total. CBF was assessed with phase-contrast MR imaging as the sum of flows in the internal carotid and vertebral arteries, and subsequent division by brain volume returned the pCBF(PCMRI) value. Accuracy was considered as good as that of the reference method if the systematic difference was less than 5 mL/min/100 g of brain tissue and if the 95% confidence intervals were equal to or better than +/- 10 mL/min/100 g. RESULTS: pCBF(ASL) correlated to pCBF(PCMRI) (r = 0.73; P < .001). Significant differences were observed between the pCBF(ASL) and pCBF(PCMRI) values in the young (P = .001) and the elderly (P < .001) volunteers. The systematic differences (mean 2 standard deviations) were -4 +/- 14 mL/min/100 g in the young subjects and 6 +/- 12 mL/min/100 g in the elderly subjects. Young subjects showed higher values than the elderly subjects for pCBF(PCMRI) (young, 57 +/- 8 mL/min/100 g; elderly, 54 +/- 7 mL/min/100 g; P = .05) and pCBF(ASL) (young, 61 +/- 10 mL/min/100 g; elderly, 48 +/- 10 mL/min/100 g; P < .001). CONCLUSIONS: The limits of agreement were too wide for the arterial spin-labeling method to be considered satisfactorily accurate, whereas the systematic overestimation in the young subjects and underestimation in the elderly subjects were close to acceptable. The age-related decrease in parenchymal CBF was augmented in arterial spin-labeling compared with phase-contrast MR imaging.

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  • 8.
    Andersson, Linus
    et al.
    Umeå University, Faculty of Social Sciences, Department of Psychology.
    Eriksson, Johan
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Stillesjö, Sara
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Social Sciences, Department of Psychology.
    Juslin, Peter
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Karlsson Wirebring, Linnea
    Umeå University, Faculty of Social Sciences, Department of Psychology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Neurocognitive processes underlying heuristic and normative probability judgments2020In: Cognition, ISSN 0010-0277, E-ISSN 1873-7838, Vol. 196, p. 1-7, article id 104153Article in journal (Refereed)
    Abstract [en]

    Judging two events in combination (A&B) as more probable than one of the events (A) is known as a conjunction fallacy. According to dual-process explanations of human judgment and decision making, the fallacy is due to the application of a heuristic, associative cognitive process. Avoiding the fallacy has been suggested to require the recruitment of a separate process that can apply normative rules. We investigated these assumptions using functional magnetic resonance imaging (fMRI) during conjunction tasks. Judgments, whether correct or not, engaged a network of brain regions identical to that engaged during similarity judgments. Avoidance of the conjunction fallacy additionally, and uniquely, involved a fronto-parietal network previously linked to supervisory, analytic control processes. The results lend credibility to the idea that incorrect probability judgments are the result of a representativeness heuristic that requires additional neurocognitive resources to avoid.

  • 9.
    Andersson, Sara
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University Hospital.
    Josefsson, Maria
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics. Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Stiernman, Lars J.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Rieckmann, Anna
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Center for the Economics of Aging, Max Planck Institute for Social Law and Social Policy, Germany.
    Cognitive decline in Parkinson’s disease: a subgroup of extreme decliners revealed by a data-driven analysis of longitudinal progression2021In: Frontiers in Psychology, E-ISSN 1664-1078, Vol. 12, article id 729755Article in journal (Refereed)
    Abstract [en]

    Cognitive impairment is an important symptom of Parkinson’s disease (PD) and predicting future cognitive decline is crucial for clinical practice. Here, we aim to identify latent sub-groups of longitudinal trajectories of cognitive change in PD patients, and explore predictors of differences in cognitive change. Longitudinal cognitive performance data from 349 newly diagnosed PD patients and 145 healthy controls from the Parkinson Progression Marker Initiative were modeled using a multivariate latent class linear mixed model. Resultant latent classes were compared on a number of baseline demographics, and clinical variables, as well as cerebrospinal fluid (CSF) biomarkers and striatal dopamine transporter (DAT) density markers of neuropathology. Trajectories of cognitive change in PD were best described by two latent classes. A large subgroup (90%), which showed a subtle impairment in cognitive performance compared to controls but remained stable over the course of the study, and a small subgroup (10%) which rapidly declined in all cognitive performance measures. Rapid decliners did not differ significantly from the larger group in terms of disease duration, severity or motor symptoms at baseline. However, rapid decliners had lower CSF amyloidß42 levels, a higher prevalence of sleep disorder and pronounced loss of caudate DAT density at baseline. These data suggest the existence of a distinct minority sub-type of PD in which rapid cognitive change in PD can occur uncoupled from motor symptoms or disease severity, likely reflecting early pathological change that extends from motor areas of the striatum into associative compartments and cortex.

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  • 10.
    Anjomshoae, Sule
    et al.
    Umeå University, Faculty of Science and Technology, Department of Computing Science. Umeå University.
    Pudas, Sara
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Explaining graph convolutional network predictions for clinicians: an explainable AI approach to Alzheimer’s disease classification2024In: Frontiers in Artificial Intelligence, E-ISSN 2624-8212, Vol. 6, article id 1334613Article in journal (Refereed)
    Abstract [en]

    Introduction: Graph-based representations are becoming more common in the medical domain, where each node defines a patient, and the edges signify associations between patients, relating individuals with disease and symptoms in a node classification task. In this study, a Graph Convolutional Networks (GCN) model was utilized to capture differences in neurocognitive, genetic, and brain atrophy patterns that can predict cognitive status, ranging from Normal Cognition (NC) to Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD), on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Elucidating model predictions is vital in medical applications to promote clinical adoption and establish physician trust. Therefore, we introduce a decomposition-based explanation method for individual patient classification.

    Methods: Our method involves analyzing the output variations resulting from decomposing input values, which allows us to determine the degree of impact on the prediction. Through this process, we gain insight into how each feature from various modalities, both at the individual and group levels, contributes to the diagnostic result. Given that graph data contains critical information in edges, we studied relational data by silencing all the edges of a particular class, thereby obtaining explanations at the neighborhood level.

    Results: Our functional evaluation showed that the explanations remain stable with minor changes in input values, specifically for edge weights exceeding 0.80. Additionally, our comparative analysis against SHAP values yielded comparable results with significantly reduced computational time. To further validate the model's explanations, we conducted a survey study with 11 domain experts. The majority (71%) of the responses confirmed the correctness of the explanations, with a rating of above six on a 10-point scale for the understandability of the explanations.

    Discussion: Strategies to overcome perceived limitations, such as the GCN's overreliance on demographic information, were discussed to facilitate future adoption into clinical practice and gain clinicians' trust as a diagnostic decision support system.

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  • 11. Athanasiu, Lavinia
    et al.
    Giddaluru, Sudheer
    Fernandes, Carla
    Christoforou, Andrea
    Reinvang, Ivar
    Lundervold, Astri J.
    Nilsson, Lars-Göran
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Aging Research Center, Karolinska Institutet, Stockholm, Sweden.
    Kauppi, Karolina
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Adolfsson, Rolf
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Psychiatry.
    Eriksson, Elias
    Sundet, Kjetil
    Djurovic, Srdjan
    Espeseth, Thomas
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Steen, Vidar M.
    Andreassen, Ole A.
    Le Hellard, Stephanie
    A genetic association study of CSMD1 and CSMD2 with cognitive function2017In: Brain, behavior, and immunity, ISSN 0889-1591, E-ISSN 1090-2139, Vol. 61, p. 209-216Article in journal (Refereed)
    Abstract [en]

    The complement cascade plays a role in synaptic pruning and synaptic plasticity, which seem to be involved in cognitive functions and psychiatric disorders. Genetic variants in the closely related CSMD1 and CSMD2 genes, which are implicated in complement regulation, are associated with schizophrenia. Since patients with schizophrenia often show cognitive impairments, we tested whether variants in CSMD1 and CSMD2 are also associated with cognitive functions per se. We took a discovery-replication approach, using well-characterized Scandinavian cohorts. A total of 1637 SNPs in CSMD1 and 206 SNPs in CSMD2 were tested for association with cognitive functions in the NCNG sample (Norwegian Cognitive NeuroGenetics; n = 670). Replication testing of SNPs with p-value < 0.001 (7 in CSMD1 and 3 in CSMD2) was carried out in the TOP sample (Thematically Organized Psychosis; n =1025) and the BETULA sample (Betula Longitudinal Study on aging, memory and dementia; n = 1742). Finally, we conducted a meta-analysis of these SNPs using all three samples. The previously identified schizophrenia marker in CSMD1 (SNP rs10503253) was also included. The strongest association was observed between the CSMDI SNP rs2740931 and performance in immediate episodic memory (p-value = 5 Chi 10(-6), minor allele A, MAF 0.48-0.49, negative direction of effect). This association reached the study-wide significance level (p <= 1.2 Chi 10(-5)). SNP rs10503253 was not significantly associated with cognitive functions in our samples. In conclusion, we studied n = 3437 individuals and found evidence that a variant in CSMD1 is associated with cognitive function. Additional studies of larger samples with cognitive phenotypes will be needed to further clarify the role of CSMD1 in cognitive phenotypes in health and disease.

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  • 12.
    Avelar-Pereira, Barbara
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
    Bäckman, Lars
    Wåhlin, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Salami, Alireza
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
    Increased functional homotopy of the prefrontal cortex is associated with corpus callosum degeneration and working memory decline2020In: Neurobiology of Aging, ISSN 0197-4580, E-ISSN 1558-1497, Vol. 96, p. 68-78Article in journal (Refereed)
    Abstract [en]

    Functional homotopy reflects the link between spontaneous activity in a voxel and its counterpart in the opposite hemisphere. Alterations in homotopic functional connectivity (FC) are seen in normal aging, with highest and lowest homotopy being present in sensory-motor and higher-order regions, respectively. Homotopic FC relates to underlying structural connections, but its neurobiological underpinnings remain unclear. The genu of the corpus callosum joins symmetrical parts of the prefrontal cortex (PFC) and is susceptible to age-related degeneration, suggesting that PFC homotopic connectivity is linked to changes in white-matter integrity. We investigated homotopic connectivity changes and whether these were associated with white-matter integrity in 338 individuals. In addition, we examined whether PFC homotopic FC was related to changes in the genu over 10 years and working memory over 5 years. There were increases and decreases in functional homotopy, with the former being prevalent in subcortical and frontal regions. Increased PFC homotopic FC was partially driven by structural degeneration and negatively associated with working memory, suggesting that it reflects detrimental age-related changes. (C) 2020 The Author(s). Published by Elsevier Inc.

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  • 13.
    Avelar-Pereira, Bárbara
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
    Backman, Lars
    Wåhlin, Anders
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Salami, Alireza
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
    Age-Related Differences in Dynamic Interactions Among Default Mode, Frontoparietal Control, and Dorsal Attention Networks during Resting-State and Interference Resolution2017In: Frontiers in Aging Neuroscience, ISSN 1663-4365, E-ISSN 1663-4365, Vol. 9, article id 152Article in journal (Refereed)
    Abstract [en]

    Resting-state fMRI (rs-fMRI) can identify large-scale brain networks, including the default mode (DMN), frontoparietal control (FPN) and dorsal attention (DAN) networks. Interactions among these networks are critical for supporting complex cognitive functions, yet the way in which they are modulated across states is not well understood. Moreover, it remains unclear whether these interactions are similarly affected in aging regardless of cognitive state. In this study, we investigated age-related differences in functional interactions among the DMN, FPN and DAN during rest and the Multi-Source Interference task (MSIT). Networks were identified using independent component analysis (ICA), and functional connectivity was measured during rest and task. We found that the FPN was more coupled with the DMN during rest and with the DAN during the MSIT. The degree of FPN-DMN connectivity was lower in older compared to younger adults, whereas no age-related differences were observed in FPN-DAN connectivity in either state. This suggests that dynamic interactions of the FPN are stable across cognitive states. The DMN and DAN were anti correlated and age-sensitive during the MSIT only, indicating variation in a task-dependent manner. Increased levels of anticorrelation from rest to task also predicted successful interference resolution. Additional analyses revealed that the degree of DMN-DAN anticorrelation during the MSIT was associated to resting cerebral blood flow (CBF) within the DMN. This suggests that reduced DMN neural activity during rest underlies an impaired ability to achieve higher levels of anticorrelation during a task. Taken together, our results suggest that only parts of age-related differences in connectivity are uncovered at rest and thus, should be studied in the functional connectome across multiple states for a more comprehensive picture.

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  • 14.
    Awad, Amar
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Blomstedt, Patric
    Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience.
    Westling, Göran
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Eriksson, Johan
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Deep brain stimulation in the caudal zona incerta modulates the sensorimotor cerebello-cerebral circuit in essential tremor2020In: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 209, article id 116511Article in journal (Refereed)
    Abstract [en]

    Essential tremor is effectively treated with deep brain stimulation (DBS), but the neural mechanisms underlying the treatment effect are poorly understood. Essential tremor is driven by a dysfunctional cerebello-thalamo-cerebral circuit resulting in pathological tremor oscillations. DBS is hypothesised to interfere with these oscillations at the stimulated target level, but it is unknown whether the stimulation modulates the activity of the cerebello-thalamo-cerebral circuit during different task states (with and without tremor) in awake essential tremor patients. To address this issue, we used functional MRI in 16 essential tremor patients chronically implanted with DBS in the caudal zona incerta. During scanning, the patients performed unilateral tremor-inducing postural holding and pointing tasks as well as rest, with contralateral stimulation turned On and Off.

    We show that DBS exerts both task-dependent as well as task-independent modulation of the sensorimotor cerebello-cerebral regions (p ​≤ ​0.05, FWE cluster-corrected for multiple comparisons). Task-dependent modulation (DBS ​× ​task interaction) resulted in two patterns of stimulation effects. Firstly, activity decreases (blood oxygen level-dependent signal) during tremor-inducing postural holding in the primary sensorimotor cortex and cerebellar lobule VIII, and activity increases in the supplementary motor area and cerebellar lobule V during rest (p ​≤ ​0.05, post hoc two-tailed t-test). These effects represent differences at the effector level and may reflect DBS-induced tremor reduction since the primary sensorimotor cortex, cerebellum and supplementary motor area exhibit less motor task-activity as compared to the resting condition during On stimulation. Secondly, task-independent modulation (main effect of DBS) was observed as activity increase in the lateral premotor cortex during all motor tasks, and also during rest (p ​≤ ​0.05, post hoc two-tailed t-test). This task-independent effect may mediate the therapeutic effects of DBS through the facilitation of the premotor control over the sensorimotor circuit, making it less susceptible to tremor entrainment.

    Our findings support the notion that DBS in essential tremor is modulating the sensorimotor cerebello-cerebral circuit, distant to the stimulated target, and illustrate the complexity of stimulation mechanisms by demonstrating task-dependent as well as task-independent actions in cerebello-cerebral regions.

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  • 15.
    Awad, Amar
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    Grill, Filip
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Blomstedt, Patric
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    Eriksson, Johan
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Deep brain stimulation does not modulate fMRI resting- state functional connectivity in essential tremorManuscript (preprint) (Other academic)
  • 16.
    Awad, Amar
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    Levi, Richard
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Rehabilitation Medicine.
    Lindgren, Lenita
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Hultling, Claes
    Department of Neurobiology, Care Sciences and Society (Neurorehabilitation), Karolinska Institute, Stockholm, Sweden.
    Westling, Göran
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Eriksson, Johan
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Preserved somatosensory conduction in a patient with complete cervical spinal cord injury2015In: Journal of Rehabilitation Medicine, ISSN 1650-1977, E-ISSN 1651-2081, Vol. 47, no 5, p. 426-431Article in journal (Refereed)
    Abstract [en]

    Objective: Neurophysiological investigation has shown that patients with clinically complete spinal cord injury can have residual motor sparing ("motor discomplete"). In the current study somatosensory conduction was assessed in a patient with clinically complete spinal cord injury and a novel ethodology for assessing such preservation is described, in this case indicating "sensory discomplete" spinal cord injury. Methods: Blood oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI) was used to examine the somatosensory system in a healthy subject and in a subject with a clinically complete cervical spinal cord injury, by applying tactile stimulation above and below the level of spinal cord injury, with and without visual feedback. Results: In the participant with spinal cord injury, somatosensory stimulation below the neurological level of the lesion gave rise to BOLD signal changes in the corresponding areas of the somatosensory cortex. Visual feedback of the stimulation strongly modulated the somatosensory BOLD signal, implying that cortico-cortical rather than spino-cortical connections can drive activity in the somatosensory cortex. Critically, BOLD signal change was also evident when the visual feedback of the stimulation was removed, thus demonstrating sensory discomplete spinal cord injury. Conclusion: Given the existence of sensory discomplete spinal cord injury, preserved but hitherto undetected somatosensory conduction might contribute to the unexplained variability related to, for example, the propensity to develop decubitus ulcers and neuropathic pain among patients with clinically complete spinal cord injury.

  • 17.
    Awad, Amar
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    Levi, Richard
    Department of Rehabilitation Medicine in Linköping, Department of Health, Medicine and Caring Sciences, Linköping University.
    Waller, Mikael
    Rehabilitation Medicine Clinic, Sunderby Hospital, Region Norrbotten.
    Westling, Göran
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    Lindgren, Lenita
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Nursing.
    Eriksson, Johan
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    Preserved somatosensory conduction in complete spinal cord injury: Discomplete SCI2020In: Clinical Neurophysiology, ISSN 1388-2457, E-ISSN 1872-8952, Vol. 131, no 5, p. 1059-1067Article in journal (Refereed)
    Abstract [en]

    Objective: Spinal cord injury (SCI) disrupts the communication between brain and body parts innervated from below-injury spinal segments, but rarely results in complete anatomical transection of the spinal cord. The aim of this study was to investigate residual somatosensory conduction in clinically complete SCI, to corroborate the concept of sensory discomplete SCI.

    Methods: We used fMRI with a somatosensory protocol in which blinded and randomized tactile and nociceptive stimulation was applied on both legs (below-injury level) and one arm (above-injury level) in eleven participants with chronic complete SCI. The experimental design accounts for possible confounding mechanical (e.g. vibration) and cortico-cortical top-down mechanisms (e.g. attention/expectation).

    Results: Somatosensory stimulation on below-level insensate body regions activated the somatotopically corresponding part of the contralateral primary somatosensory cortex in six out of eleven participants.

    Conclusions: Our results represent afferent-driven cortical activation through preserved somatosensory connections to the brain in a subgroup of participants with clinically complete SCI, i.e. sensory discomplete SCI.

    Significance: Identifying patients with residual somatosensory connections might open the door for new rehabilitative and restorative strategies as well as inform research on SCI-related conditions such as neuropathic pain and spasticity.

  • 18.
    Backeström, Anna
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Papadopoulos, Konstantin
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Eriksson, Sture
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Nutritional Research.
    Olsson, Tommy
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Medicine.
    Andersson, Micael
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Blennow, Kaj
    Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at University of Gothenburg, Mö lndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mö lndal, Sweden.
    Zetterberg, Henrik
    Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mö lndal, Sweden; Department of Neurodegenerative Disease, Ucl Institute of Neurology, Queen Square, London, United Kingdom; UK Dementia Research Institute at Ucl, London, United Kingdom.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Rolandsson, Olov
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Acute hyperglycaemia leads to altered frontal lobe brain activity and reduced working memory in type 2 diabetes2021In: PLOS ONE, E-ISSN 1932-6203, Vol. 16, no 3, article id e0247753Article in journal (Refereed)
    Abstract [en]

    How acute hyperglycaemia affects memory functions and functional brain responses in individuals with and without type 2 diabetes is unclear. Our aim was to study the association between acute hyperglycaemia and working, semantic, and episodic memory in participants with type 2 diabetes compared to a sex- A nd age-matched control group. We also assessed the effect of hyperglycaemia on working memory-related brain activity. A total of 36 participants with type 2 diabetes and 34 controls (mean age, 66 years) underwent hyperglycaemic clamp or placebo clamp in a blinded and randomised order. Working, episodic, and semantic memory were tested. Overall, the control group had higher working memory (mean z-score 33.15 ± 0.45) than the group with type 2 diabetes (mean z-score 31.8 ± 0.44, p = 0.042) considering both the placebo and hyperglycaemic clamps. Acute hyperglycaemia did not influence episodic, semantic, or working memory performance in either group. Twenty-two of the participants (10 cases, 12 controls, mean age 69 years) were randomly invited to undergo the same clamp procedures to challenge working memory, using 1-, 2-, and 3-back, while monitoring brain activity by blood oxygen level-dependent functional magnetic resonance imaging (fMRI). The participants with type 2 diabetes had reduced working memory during the 1- A nd 2-back tests. fMRI during placebo clamp revealed increased BOLD signal in the left lateral frontal cortex and the anterior cingulate cortex as a function of working memory load in both groups (3>2>1). During hyperglycaemia, controls showed a similar load-dependent fMRI response, whereas the type 2 diabetes group showed decreased BOLD response from 2-to 3-back. These results suggest that impaired glucose metabolism in the brain affects working memory, possibly by reducing activity in important frontal brain areas in persons with type 2 diabetes.

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  • 19.
    Backman, Lars
    et al.
    Aging Research Center, Karolinska Institute and University of Stockholm, Stockholm,.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Dopamine and training-related working-memory improvement2013In: Neuroscience and Biobehavioral Reviews, ISSN 0149-7634, E-ISSN 1873-7528, Vol. 37, no 9, p. 2209-2219Article, review/survey (Refereed)
    Abstract [en]

    Converging evidence indicates that the neurotransmitter dopamine (DA) is implicated in working-memory (WM) functioning and that WM is trainable. We review recent work suggesting that DA is critically involved in the ability to benefit from WM interventions. Functional MRI studies reveal increased striatal BOLD activity following certain forms of WM interventions, such as updating training. Increased striatal BOLD activity has also been linked to transfer of learning to non-trained WM tasks, suggesting a neural signature of transfer. The striatal BOLD signal is partly determined by DA activity. Consistent with this assertion, PET research demonstrates increased striatal DA release during updating of information in WM after training. Genetic studies indicate larger increases in WM performance post training for those who carry advantageous alleles of DA-relevant genes. These patterns of results corroborate the role of DA in WM improvement. Future research avenues include: (a) neuromodulatory correlates of transfer; (b) the potential of WM training to enhance DA release in older adults; (c) comparisons among different WM processes (i.e., updating, switching, inhibition) regarding regional patterns of training-related DA release; and (d) gene-gene interactions in relation to training-related WM gains.

  • 20. Bangsbo, Jens
    et al.
    Blackwell, Joanna
    Boraxbekk, Carl-Johan
    Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). DRCMR, University of Copenhagen, Denmark.
    Caserotti, Paolo
    Dela, Flemming
    Evans, Adam B.
    Jespersen, Astrid Pernille
    Gliemann, Lasse
    Kramer, Arthur F.
    Lundbye-Jensen, Jesper
    Lykke Mortensen, Erik
    Juul Lassen, Aske
    Gow, Alan J.
    Harridge, Stephen D.R.
    Hellsten, Ylva
    Kjaer, Michael
    Kujala, Urho M.
    Rhodes, Ryan E.
    Pike, Elizabeth C.J.
    Skinner, Timothy
    Skovgaard, Thomas
    Troelsen, Jens
    Tulle, Emmanuelle
    Tully, Mark A.
    van Uffelen, Jannique G.Z.
    Viña, Jose
    Copenhagen Consensus statement 2019: physical activity and ageing2019In: British Journal of Sports Medicine, ISSN 0306-3674, E-ISSN 1473-0480, Vol. 53, no 14, p. 856-858Article in journal (Refereed)
    Abstract [en]

    From 19th to 22nd November 2018, 26 researchers representing nine countries and a variety of academic disciplines met in Snekkersten, Denmark, to reach evidence-based consensus about physical activity and older adults. It was recognised that the term ‘older adults’ represents a highly heterogeneous population. It encompasses those that remain highly active and healthy throughout the life-course with a high intrinsic capacity to the very old and frail with low intrinsic capacity. The consensus is drawn from a wide range of research methodologies within epidemiology, medicine, physiology, neuroscience, psychology and sociology, recognising the strength and limitations of each of the methods. Much of the evidence presented in the statements is based on longitudinal associations from observational and randomised controlled intervention studies, as well as quantitative and qualitative social studies in relatively healthy community-dwelling older adults. Nevertheless, we also considered research with frail older adults and those with age-associated neurodegenerative diseases, such as Alzheimer’s and Parkinson’s disease, and in a few cases molecular and cellular outcome measures from animal studies. The consensus statements distinguish between physical activity and exercise. Physical activity is used as an umbrella term that includes both structured and unstructured forms of leisure, transport, domestic and work-related activities. Physical activity entails body movement that increases energy expenditure relative to rest, and is often characterised in terms of intensity from light, to moderate to vigorous. Exercise is defined as a subset of structured physical activities that are more specifically designed to improve cardiorespiratory fitness, cognitive function, flexibility balance, strength and/or power. This statement presents the consensus on the effects of physical activity on older adults’ fitness, health, cognitive functioning, functional capacity, engagement, motivation, psychological well-being and social inclusion. It also covers the consensus on physical activity implementation strategies. While it is recognised that adverse events can occur during exercise, the risk can be minimised by carefully choosing the type of activity undertaken and by consultation with the individual’s physician when warranted, for example, when the individual is frail, has a number of co-morbidities, or has exercise-related symptoms, such as chest pain, heart arrhythmia or dizziness. The consensus was obtained through an iterative process that began with the presentation of the state-of-the-science in each domain, followed by group and plenary discussions. Ultimately, the participants reached agreement on the 30-item consensus statements.

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  • 21. Bas-Hoogendam, Janna Marie
    et al.
    van Steenbergen, Henk
    Pannekoek, J. Nienke
    Fouche, Jean-Paul
    Lochner, Christine
    Hattingh, Coenraad J.
    Cremers, Henk R.
    Furmark, Tomas
    Månsson, Kristoffer
    Frick, Andreas
    Engman, Jonas
    Boraxbekk, Carl-Johan
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Carlbring, Per
    Andersson, Gerhard
    Fredriksson, Mats
    Straube, Thomas
    Peterburs, Jutta
    Klumpp, Heide
    Phan, K. Luan
    Roelofs, Karin
    Veltman, Dick J.
    van Tol, Marie-Jose
    Stein, Dan J.
    van der Wee, Nic J. A.
    Voxel-based morphometry multi-center mega-analysis of brain structure in social anxiety disorder2017In: NeuroImage: Clinical, E-ISSN 2213-1582, Vol. 16, p. 678-688Article in journal (Refereed)
    Abstract [en]

    Social anxiety disorder (SAD) is a prevalent and disabling mental disorder, associated with significant psychiatric comorbidity. Previous research on structural brain alterations associated with SAD has yielded inconsistent results concerning the direction of the changes in graymatter (GM) in various brain regions, as well as on the relationship between brain structure and SAD-symptomatology. These heterogeneous findings are possibly due to limited sample sizes. Multisite imaging offers new opportunities to investigate SAD-related alterations in brain structure in larger samples. An international multi-center mega-analysis on the largest database of SAD structural T1-weighted 3T MRI scans to date was performed to compare GM volume of SAD-patients (n = 174) and healthy control (HC)-participants (n = 213) using voxel-based morphometry. A hypothesis-driven region of interest (ROI) approach was used, focusing on the basal ganglia, the amygdala-hippocampal complex, the prefrontal cortex, and the parietal cortex. SAD-patients had larger GM volume in the dorsal striatum when compared to HC-participants. This increase correlated positively with the severity of self-reported social anxiety symptoms. No SAD-related differences in GM volume were present in the other ROIs. Thereby, the results of this mega-analysis suggest a role for the dorsal striatum in SAD, but previously reported SAD-related changes in GM in the amygdala, hippocampus, precuneus, prefrontal cortex and parietal regions were not replicated. Our findings emphasize the importance of large sample imaging studies and the need for meta-analyses like those performed by the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium.

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  • 22. Becker, Nina
    et al.
    Kalpouzos, Grégoria
    Salami, Alireza
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Wallenberg Centre for Molecular Medicine at Umeå University (WCMM). Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
    Laukka, Erika J.
    Brehmer, Yvonne
    Structure-function associations of successful associative encoding2019In: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 201, article id 116020Article in journal (Refereed)
    Abstract [en]

    Functional magnetic resonance imaging (MRI) studies have demonstrated a critical role of hippocampus and inferior frontal gyrus (IFG) in associative memory. Similarly, evidence from structural MRI studies suggests a relationship between gray-matter volume in these regions and associative memory. However, how brain volume and activity relate to each other during associative-memory formation remains unclear. Here, we used joint independent component analysis (jICA) to examine how gray-matter volume and brain activity would be associated during associative encoding, especially in medial-temporal lobe (MTL) and IFG. T1-weighted images were collected from 27 young adults, and functional MRI was employed during intentional encoding of object pairs. A subsequent recognition task tested participants' memory performance. Unimodal analyses using voxel-based morphometry revealed that participants with better associative memory showed larger gray-matter volume in left anterior hippocampus. Results from the jICA revealed one component that comprised a covariance pattern between gray-matter volume in anterior and posterior MTL and encoding-related activity in IFG. Our findings suggest that gray matter within the MTL modulates distally distinct parts of the associative encoding circuit, and extend previous studies that demonstrated MTL-IFG functional connectivity during associative memory tasks.

  • 23.
    Bergdahl, Jan
    et al.
    Umeå University, Faculty of Social Sciences, Department of Psychology.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Nilsson, Lars-Göran
    Riklund Åhlström, Katrine
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Nyberg, Lars
    Umeå University, Faculty of Social Sciences, Department of Psychology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Treatment of chronic stress in employees: subjective, cognitive and neural correlates2005In: Scandinavian Journal of Psychology, ISSN 0036-5564, E-ISSN 1467-9450, Vol. 46, no 5, p. 395-402Article in journal (Refereed)
    Abstract [en]

    This study reports the effect of an affect-focused intervention program, the Affect School, on stress, psychological symptoms, cognitive functioning and neural activity. Fifty employees in social service and education, with high levels of chronic stress, were randomly divided into a treatment (N= 27) and control (N= 23) group. Complete sets of data were available in 20 participants in the treatment group and 17 in the control group. The Perceived Stress Questionnaire assessed stress and the Symptom Check List-90 psychological symptoms before and after treatment. Episodic-memory functioning under focused and divided attention conditions was also assessed. Prior and after the Affect School, seven participants in the treatment group were studied with functional magnetic resonance imaging (fMRI) during episodic memory processing. After the Affect School there was a reduction in stress and psychological symptoms for the treatment group but not in the control group. The controls showed a reduction in episodic memory functioning whereas the performance of the treatment group remained intact. The fMRI scanning indicated a qualitative change in the neural network subserving episodic memory. These preliminary results suggest that the Affect School is effective on individuals with high stress.

  • 24.
    Berginström, Nils
    et al.
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine.
    Nordström, Peter
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine.
    Ekman, Urban
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Karolinska Inst, Dept Neurobiol Care Sci & Soc, Stockholm, Sweden.
    Eriksson, Johan
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Andersson, Micael
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Nordström, Anna
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine.
    Fatigue after traumatic brain injury is linked to altered striato-thalamic-cortical functioning2017In: Brain Injury, ISSN 0269-9052, E-ISSN 1362-301X, Vol. 31, no 6-7, p. 755-755Article in journal (Refereed)
    Abstract [en]

    Mental fatigue is a common symptom in the chronic phase of traumatic brain injury. Despite its high prevalence, no treatmentis available for this disabling symptom, and the mechanisms underlying fatigue are poorly understood. Some studies have suggested that fatigue in traumatic brain injury and other neurological disorders might reflect dysfunction within striato-thalamic-cortical loops. In the present study, we investigated whether functional magnetic resonance imaging(fMRI) can be used to detect chronic fatigue after traumatic brain injury (TBI), with emphasis on the striato-thalamic cortical-loops. We included patients who had suffered traumatic brain injury (n = 57, age range 20–64 years) and experienced mental fatigue > 1 year post injury (mean = 8.79 years, SD = 7.35), and age- and sex-matched healthycontrols (n = 27, age range 25–65 years). All participants completed self-assessment scales of fatigue and other symptoms, underwent an extensive neuropsychological test battery and performed a fatiguing 27-minute attention task (the modified Symbol Digit Modalities Test) during fMRI. Accuracy did not differ between groups, but reaction times were slower in the traumatic brain injury group (p < 0.001). Patients showed a greater increase in fatigue than controls from before to after task completion (p < 0.001). Patients showed less fMRI blood oxygen level–dependent activity in several a priori hypothesized regions (family-wise error corrected,p < 0.05), including the bilateral caudate, thalamus and anterior insula. Using the left caudate as a region of interest and testing for sensitivity and specificity, we identified 91% of patients and 81% of controls. As expected, controls showed decreased activation over time in regions of interest—the bilateral caudate and anterior thalamus (p < 0.002, uncorrected)—whereas patients showed no corresponding activity decrease. These results suggest that chronic fatigue after TBI is linked to altered striato-thalamic-cortical functioning. The high precision of fMRI for the detection of fatigue is of great clinical interest, given the lack of objective measures for the diagnosis of fatigue.

  • 25.
    Berginström, Nils
    et al.
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine.
    Nordström, Peter
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine.
    Ekman, Urban
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Karolinska Inst, Dept Neurobiol Care Sci & Soc, Stockholm, Sweden.
    Eriksson, Johan
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    Andersson, Micael
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    Nordström, Anna
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine. Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine.
    Using Functional Magnetic Resonance Imaging to Detect Chronic Fatigue in Patients With Previous Traumatic Brain Injury: changes linked to altered Striato-Thalamic-Cortical Functioning2018In: The journal of head trauma rehabilitation, ISSN 0885-9701, E-ISSN 1550-509X, Vol. 33, no 4, p. 266-274Article in journal (Refereed)
    Abstract [en]

    Objective: To investigate whether functional magnetic resonance imaging (fMRI) can be used to detect fatigue after traumatic brain injury (TBI).

    Setting: Neurorehabilitation clinic.

    Participants: Patients with TBI (n = 57) and self-experienced fatigue more than 1 year postinjury, and age- and gender-matched healthy controls (n = 27).

    Main Measures: Self-assessment scales of fatigue, a neuropsychological test battery, and fMRI scanning during performance of a fatiguing 27-minute attention task.

    Results: During testing within the fMRI scanner, patients showed a higher increase in self-reported fatigue than controls from before to after completing the task (P < .001).The patients also showed lower activity in several regions, including bilateral caudate, thalamus, and anterior insula (all P < .05). Furthermore, the patients failed to display decreased activation over time in regions of interest: the bilateral caudate and anterior thalamus (all P < .01). Left caudate activity correctly identified 91% of patients and 81% of controls, resulting in a positive predictive value of 91%.

    Conclusion: The results suggest that chronic fatigue after TBI is associated with altered striato-thalamic-cortical functioning. It would be of interest to study whether fMRI can be used to support the diagnosis of chronic fatigue in future studies.

  • 26.
    Berginström, Nils
    et al.
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine.
    Nordström, Peter
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine. School of Sport Sciences, The Arctic University of Norway, Tromsø, Norway Medicine.
    Ekman, Urban
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
    Eriksson, Johan
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Nordström, Anna
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Sustainable Health. School of Sport Sciences, The Arctic University of Norway, Tromsø, Norway.
    Pharmaco-fMRI in Patients With Traumatic Brain Injury: A Randomized Controlled Trial With the Monoaminergic Stabilizer (-)-OSU61622019In: The journal of head trauma rehabilitation, ISSN 0885-9701, E-ISSN 1550-509X, Vol. 34, no 3, p. 189-198Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: To examine the effects of monoaminergic stabilizer (-)-OSU6162 on brain activity, as measured by blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI), in patients in the chronic phase of traumatic brain injury suffering from fatigue.

    SETTING: Neurorehabilitation clinic.

    PARTICIPANTS: Patients with traumatic brain injury received either placebo (n = 24) or active treatment (n = 28). Healthy controls (n = 27) went through fMRI examination at one point and were used in sensitivity analysis on normalization of BOLD response.

    DESIGN: Randomized, double-blinded, placebo-controlled design.

    MAIN MEASURES: Effects on BOLD signal changes from before to after treatment during performance of a fatiguing attention task.

    RESULTS: The fMRI results revealed treatment effects within the right occipitotemporal cortex and the right orbitofrontal cortex. In these regions, the BOLD response was normalized relative to healthy controls at the postintervention fMRI session. No effects were seen in regions in which we previously observed activity differences between patients and healthy controls while performing this fMRI task, such as the striatum.

    CONCLUSION: (-)-OSU6162 treatment had influences on functional brain activity, although the normalized regional BOLD response was observed in regions that were not a priori hypothesized to be sensitive to this particular treatment, and was not accompanied by any effects on in-scanner test performance or on fatigue.

  • 27.
    Berginström, Nils
    et al.
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine. Umeå University, Faculty of Social Sciences, Department of Psychology.
    Nordström, Peter
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Nordström, Anna
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Sustainable Health. School of Sport Sciences, The Arctic University of Norway, Tromsø, Norway..
    White matter hyperintensities increases with traumatic brain injury severity: associations to neuropsychological performance and fatigue2020In: Brain Injury, ISSN 0269-9052, E-ISSN 1362-301X, Vol. 34, no 3, p. 415-420Article in journal (Refereed)
    Abstract [en]

    Objective: To examine the prevalence of white matter hyperintensities (WMHs) in patients with traumatic brain injury (TBI) as compared to healthy controls, and to investigate whether there is an association between WMH lesion burden and performance on neuropsychological tests in patients with TBI.

    Methods: A total of 59 patients with TBI and 27 age- and gender-matched healthy controls underwent thorough neuropsychological testing and magnetic resonance imaging. The quantification of WMH lesions was performed using the fully automated Lesion Segmentation Tool.

    Results: WMH lesions were more common in patients with TBI than in healthy controls (p = .032), and increased with higher TBI severity (p = .025). Linear regressions showed that WMH lesions in patients with TBI were not related to performance on any neuropsychological tests (p > .05 for all). However, a negative relationship between number of WMH lesions in patients with TBI and self-assessed fatigue was found (r = - 0.33, p = .026).

    Conclusion: WMH lesions are more common in patients with TBI than in healthy controls, and WMH lesions burden increases with TBI severity. These lesions could not explain decreased cognitive functioning in patients with TBI but did relate to decreased self-assessment of fatigue after TBI.

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  • 28.
    Bergman, Frida
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Boraxbekk, Carl-Johan
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Wennberg, Patrik
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Sörlin, Ann
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Physiotherapy.
    Olsson, Tommy
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Increasing physical activity in officeworkers – the Inphact Treadmill study: a study protocol for a 13-month randomized controlled trial of treadmill workstations2015In: BMC Public Health, E-ISSN 1471-2458, Vol. 15, article id 632Article in journal (Refereed)
    Abstract [en]

    Background: Sedentary behaviour is an independent risk factor for mortality and morbidity, especially for type 2 diabetes. Since office work is related to long periods that are largely sedentary, it is of major importance to find ways for office workers to engage in light intensity physical activity (LPA). The Inphact Treadmill study aims to investigate the effects of installing treadmill workstations in offices compared to conventional workstations.

    Methods/Design: A two-arm, 13-month, randomized controlled trial (RCT) will be conducted. Healthy overweight and obese office workers (n = 80) with mainly sedentary tasks will be recruited from office workplaces in Umeå, Sweden. The intervention group will receive a health consultation and a treadmill desk, which they will use for at least one hour per day for 13 months. The control group will receive the same health consultation, but continue to work at their regular workstations. Physical activity and sedentary time during workdays and non-workdays as well as during working and non-working hours on workdays will be measured objectively using accelerometers (Actigraph and activPAL) at baseline and after 2, 6, 10, and 13 months of follow-up. Food intake will be recorded and metabolic and anthropometric variables, body composition, stress, pain, depression, anxiety, cognitive function, and functional magnetic resonance imaging will be measured at 3–5 time points during the study period. Interviews with participants from the intervention group will be performed at the end of the study.

    Discussion: This will be the first long-term RCT on the effects of treadmill workstations on objectively measured physical activity and sedentary time as well as other body functions and structures/morphology during working and non-working hours among office workers. This will provide further insight on the effects of active workstations on our health and could fill in some of the knowledge gaps regarding how we can reduce sedentary time in office environments.

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  • 29.
    Bergman, Frida
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Matsson-Frost, Tove
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Jonasson, Lars S.
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Chorell, Elin
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Medicine.
    Sörlin, Ann
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation.
    Wennberg, Patrik
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Öhberg, Fredrik
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Ryberg, Mats
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Medicine.
    Levine, James A
    Mayo Clinic Rochester MN, USA; Fondation IPSEN, Paris, France.
    Olsson, Tommy
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Section of Medicine.
    Boraxbekk, Carl-Johan
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Danish Research Center for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital, Hvidovre, Denmark; Institute of Sports Medicine Copenhagen (ISMC), Copenhagen University Hospital, Copenhagen, Denmark.
    Walking Time Is associated With Hippocampal Volume in Overweight and Obese Office Workers2020In: Frontiers in Human Neuroscience, E-ISSN 1662-5161, Vol. 14, article id 307Article in journal (Refereed)
    Abstract [en]

    Objectives: To investigate the long-term effects on cognition and brain function after installing treadmill workstations in offices for 13 months.

    Methods: Eighty healthy overweight or obese office workers aged 40–67 years were individually randomized to an intervention group, receiving a treadmill workstation and encouraging emails, or to a control group, continuing to work as usual. Effects on cognitive function, hippocampal volume, prefrontal cortex (PFC) thickness, and circulating brain-derived neurotrophic factor (BDNF) were analyzed. Further, mediation analyses between changes in walking time and light-intensity physical activity (LPA) on changes in BDNF and hippocampal volume between baseline and 13 months, and multivariate analyses of the baseline data with percentage sitting time as the response variable, were performed.

    Results: No group by time interactions were observed for any of the outcomes. In the mediation analyses, positive associations between changes in walking time and LPA on changes in hippocampal volume were observed, although not mediated by changes in BDNF levels. In the multivariate analyses, a negative association between percentage sitting time and hippocampal volume was observed, however only among those older than 51 years of age.

    Conclusion: Although no group by time interactions were observed, our analyses suggest that increased walking and LPA may have positive effects on hippocampal volume and that sedentary behavior is associated with brain structures of importance for memory functions.

    Trial Registration: www.ClinicalTrials.gov as NCT01997970.

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  • 30.
    Bergman, Frida
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Mattson-Frost, Tove
    Jonasson, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Chorell, Elin
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Sörlin, Ann
    Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Physiotherapy.
    Wennberg, Patrik
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Family Medicine.
    Öhberg, Fredrik
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Ryberg, Mats
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Levine, James
    Olsson, Tommy
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Boraxbekk, Carl-Johan
    Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Installing treadmill workstations in offices does little for cognitive performance and brain structure, despite a baseline association between sitting time and hippocampus volumeManuscript (preprint) (Other academic)
  • 31.
    Bergouignan, Loretxu
    et al.
    BCBL, Basque Center on Cognition, Brain and Language, Donostia, Spain.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Ehrsson, H. Henrik
    Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden.
    Out-of-body memory encoding causes third-person perspective at recall2022In: Journal of Cognitive Psychology, ISSN 2044-5911, E-ISSN 2044-592X, Vol. 34, no 1, p. 160-178Article in journal (Refereed)
    Abstract [en]

    Sigmund Freud famously noted some memories are recalled with a perspective of “an observer from outside the scene”. According to Freud—and most memory researchers today—the third-person perspective occurs due to reconstructive processes at recall. An alternative possibility is that the third-person perspective have been adopted when the actual event is experienced and later recalled in its original form. Here we test this hypothesis using a perceptual out-of-body illusion during the encoding of real events. Participants took part in a social interaction while experiencing an out-of-body illusion where they viewed the event and their own body from a third-person perspective. In recall sessions ∼1 week later, events encoded in the out-of-body compared to the in-body control condition were significantly less recalled from a first-person perspective. An out-of-body experience leads to more third-person perspective during recollection.

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  • 32.
    Bergström, Fredrik
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    The neural substrates of non-conscious working memory2016Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Background: Despite our distinct impression to the contrary, we are only conscious of a fraction of all the neural activity underlying our thoughts and behavior. Most neural processes occur non-consciously, and in parallel with our conscious experience. However, it is still unclear what the limits of non-conscious processes are in terms of higher cognitive functions. Many recent studies have shown that increasingly more advanced functions can operate non-consciously, but non-conscious information is still thought to be fleeting and undetectable within 500 milliseconds. Here we used various techniques to render information non-conscious, together with functional magnetic resonance imaging (fMRI), to investigate if non-consciously presented information can be retained for several seconds, what the neural substrates of such retention are, and if it is consistent with working memory maintenance.

    Results: In Study I we used an attentional blink paradigm to render stimuli (single letters) non-conscious, and a variable delay period (5 – 15 s) prior to memory test. It was found that non-conscious memory performance was above chance after all delay durations, and showed no signs of decline over time. Univariate fMRI analysis showed that the durable retention was associated with sustained BOLD signal change in the prefrontal cortex and cerebellum during the delay period. In Study II we used continuous flash suppression (CFS) to render stimuli (faces and tools) non-conscious, and a variable delay period (5 or 15 s) prior to memory test. The durable retention of up to 15 s was replicated, and it was found that stimuli identity and spatial position was retained until prospective use. In Study III we used CFS to render tools non-conscious, and a variable delay period (5 – 15 s) prior to memory test. It was found that memory performance was not better than chance. However, by using multi-voxel pattern analysis it was nonetheless possible to detect the presence vs. absence of non-conscious stimuli in the frontal cortex,and their spatial position (left vs. right) in the occipital cortex during the delay.

    Conclusions: Overall these findings suggest that non-consciously presented information (identity and/or position) can be retained for several seconds,and is associated with BOLD signal in frontal and posterior regions. These findings are consistent with working memory maintenance of non-consciously presented information, and thereby constrain models of working memory and theories of consciousness.

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  • 33.
    Bergström, Fredrik
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Eriksson, Johan
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Maintenance of non-consciously presented information engages the prefrontal cortex2014In: Frontiers in Human Neuroscience, E-ISSN 1662-5161, Vol. 8, p. 938-Article in journal (Refereed)
    Abstract [en]

    Conscious processing is generally seen as required for flexible and willful actions, as well as for tasks that require durable information maintenance. Here we present research that questions the assumption that only consciously perceived information is durable (>500 ms). Using the attentional blink (AB) phenomenon, we rendered otherwise relatively clearly perceived letters non conscious. In a first experiment we systematically manipulated the delay between stimulus presentation and response, for the purpose of estimating the durability of non-conscious perceptual representations. For items reported not seen, we found that behavioral performance was better than chance across intervals up to 15 s. In a second experiment we used fMRI to investigate the neural correlates underlying the maintenance of non conscious perceptual representations. Critically, the relatively long delay period demonstrated in experiment 1 enabled isolation of the signal change specifically related to the maintenance period, separate from stimulus presentation and response. We found sustained BOLD signal change in the right mid-lateral prefrontal cortex, orbitofrontal cortex, and crus II of the cerebellum during maintenance of non consciously perceived information. These findings are consistent with the controversial claim that working-memory mechanisms are involved in the short-term maintenance of non-conscious perceptual representations.

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  • 34.
    Bergström, Fredrik
    et al.
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Faculty of Psychology and Educational Sciences, University of Coimbra, Portugal.
    Eriksson, Johan
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Neural evidence for non-conscious working memory2018In: Cerebral Cortex, ISSN 1047-3211, E-ISSN 1460-2199, Vol. 28, no 9, p. 3217-3228Article in journal (Refereed)
    Abstract [en]

    Recent studies have found that non-consciously perceived information can be retained for several seconds, a feat that has been attributed to non-conscious working memory processes. However, these studies have mainly relied on subjective measures of visual experience, and the neural processes responsible for non-conscious short-term retention remains unclear. Here we used continuous flash suppression to render stimuli non-conscious in a delayed match-to-sample task together with fMRI to investigate the neural correlates of non-conscious short-term (5-15 s) retention. The participants' behavioral performance was at chance level when they reported no visual experience of the sample stimulus. Critically, multivariate pattern analyses of BOLD signal during the delay phase could classify presence versus absence of sample stimuli based on signal patterns in frontal cortex, and its spatial position based on signal patterns in occipital cortex. In addition, univariate analyses revealed increased BOLD signal change in prefrontal regions during memory recognition. Thus, our findings demonstrate short-term maintenance of information presented non-consciously, defined by chance performance behaviorally. This non-consciously retained information seems to rely on persistent neural activity in frontal and occipital cortex, and may engage further cognitive control processes during memory recognition.

  • 35.
    Bergström, Fredrik
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Eriksson, Johan
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology.
    The conjunction of non-consciously perceived object identity and spatial position can be retained during a visual short-term memory task2015In: Frontiers in Psychology, E-ISSN 1664-1078, Vol. 6, article id 1470Article in journal (Refereed)
    Abstract [en]

    Although non-consciously perceived information has previously been assumed to be short-lived (<500 ms), recent findings show that non-consciously perceived information can be maintained for at least 15s Such findings can be explained as working memory without a conscious experience of the information to be retained. However, whether or not working memory can operate on non-consciously perceived information remains controversial, and little is known about the nature of such non-conscious visual short-term memory (VSTM). Here we used continuous flash suppression to render stimuli non-conscious, to investigate the properties of non-consciously perceived representations in delayed match-to-sample (DMS) tasks. In Experiment I we used variable delays (5 or 15s) and found that performance was significantly better than chance and was unaffected by delay duration, thereby replicating previous findings. In Experiment II the DMS task required participants to combine information of spatial position and object identity on a trial-by-trial basis to successfully solve the task. We found that the conjunction of spatial position and object identity was retained, thereby verifying that non-conscious, trial-specific information can be maintained for prospective use. We conclude that our results are consistent with a working memory interpretation, but that more research is needed to verify this interpretation.

  • 36.
    Binnewies, Julia
    et al.
    Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, Netherlands.
    Nawijn, Laura
    Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, Netherlands.
    Brandmaier, Andreas M.
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck, UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany; Department of Psychology, MSB Medical School Berlin, Berlin, Germany.
    Baaré, William F.C.
    Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital – Amager and Hvidovre, Copenhagen, Denmark.
    Bartrés-Faz, David
    Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona and Institut de Neurociències, Universitat de Barcelona, Spain.
    Drevon, Christian A.
    Department of Nutrition, Institute of Basic Medical Sciences, Faculty of Medicine, University of Oslo & Vitas Ltd, Oslo Science Park, Oslo, Norway.
    Düzel, Sandra
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck, UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany.
    Fjell, Anders M.
    Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway.
    Han, Laura K.M.
    Centre for Youth Mental Health, The University of Melbourne, VIC, Parkville, Australia.
    Knights, Ethan
    MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom.
    Lindenberger, Ulman
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck, UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany.
    Milaneschi, Yuri
    Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, Netherlands.
    Mowinckel, Athanasia M.
    Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Plachti, Anna
    Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital – Amager and Hvidovre, Copenhagen, Denmark.
    Madsen, Kathrine Skak
    Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital – Amager and Hvidovre, Copenhagen, Denmark; Radiography, Department of Technology, University College Copenhagen, Copenhagen, Denmark.
    Solé-Padullés, Cristina
    Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona and Institut de Neurociències, Universitat de Barcelona, Spain.
    Suri, Sana
    Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom; Department of Psychiatry, University of Oxford, United Kingdom.
    Walhovd, Kristine B.
    Center for Lifespan Changes in Brain and Cognition, University of Oslo, Norway; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway.
    Zsoldos, Enikő
    Wellcome Centre for Integrative Neuroimaging, University of Oxford, United Kingdom; Department of Psychiatry, University of Oxford, United Kingdom.
    Ebmeier, Klaus P.
    Department of Psychiatry, University of Oxford, United Kingdom.
    Penninx, Brenda W.J.H.
    Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, Netherlands.
    Associations of depression and regional brain structure across the adult lifespan: Pooled analyses of six population-based and two clinical cohort studies in the European Lifebrain consortium2022In: NeuroImage: Clinical, E-ISSN 2213-1582, Vol. 36, article id 103180Article in journal (Refereed)
    Abstract [en]

    Objective: Major depressive disorder has been associated with lower prefrontal thickness and hippocampal volume, but it is unknown whether this association also holds for depressive symptoms in the general population. We investigated associations of depressive symptoms and depression status with brain structures across population-based and patient-control cohorts, and explored whether these associations are similar over the lifespan and across sexes.

    Methods: We included 3,447 participants aged 18–89 years from six population-based and two clinical patient-control cohorts of the European Lifebrain consortium. Cross-sectional meta-analyses using individual person data were performed for associations of depressive symptoms and depression status with FreeSurfer-derived thickness of bilateral rostral anterior cingulate cortex (rACC) and medial orbitofrontal cortex (mOFC), and hippocampal and total grey matter volume (GMV), separately for population-based and clinical cohorts.

    Results: Across patient-control cohorts, depressive symptoms and presence of mild-to-severe depression were associated with lower mOFC thickness (rsymptoms = −0.15/ rstatus = −0.22), rACC thickness (rsymptoms = −0.20/ rstatus = −0.25), hippocampal volume (rsymptoms = −0.13/ rstatus = 0.13) and total GMV (rsymptoms = −0.21/ rstatus = −0.25). Effect sizes were slightly larger for presence of moderate-to-severe depression. Associations were similar across age groups and sex. Across population-based cohorts, no associations between depression and brain structures were observed.

    Conclusions: Fitting with previous meta-analyses, depressive symptoms and depression status were associated with lower mOFC, rACC thickness, and hippocampal and total grey matter volume in clinical patient-control cohorts, although effect sizes were small. The absence of consistent associations in population-based cohorts with mostly mild depressive symptoms, suggests that significantly lower thickness and volume of the studied brain structures are only detectable in clinical populations with more severe depressive symptoms.

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  • 37.
    Binnewies, Julia
    et al.
    Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress program, Amsterdam, Netherlands.
    Nawijn, Laura
    Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress program, Amsterdam, Netherlands.
    Brandmaier, Andreas M.
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany; Department of Psychology, MSB Medical School Berlin, Berlin, Germany.
    Baaré, William F.C.
    Danish Research Centre for Magnetic Resonance, centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark.
    Boraxbekk, Carl-Johan
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Danish Research Centre for Magnetic Resonance, centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark; Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark; Institute of Sports Medicine Copenhagen (ISMC) and Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark.
    Demnitz, Naiara
    Danish Research Centre for Magnetic Resonance, centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark.
    Drevon, Christian A.
    Vitas Ltd. Oslo Science Park & Department of Nutrition, IMB, University of Oslo, Norway.
    Fjell, Anders M.
    Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway; Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway.
    Lindenberger, Ulman
    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany.
    Madsen, Kathrine Skak
    Danish Research Centre for Magnetic Resonance, centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Topiwala, Anya
    Nuffield Department of Population Health, Big Data Institute, University of Oxford, Oxford, United Kingdom.
    Walhovd, Kristine B.
    Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway; Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Norway.
    Ebmeier, Klaus P.
    Department of Psychiatry, University of Oxford, United Kingdom.
    Penninx, Brenda W.J.H.
    Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress program, Amsterdam, Netherlands.
    Lifestyle-related risk factors and their cumulative associations with hippocampal and total grey matter volume across the adult lifespan: a pooled analysis in the European Lifebrain consortium2023In: Brain Research Bulletin, ISSN 0361-9230, E-ISSN 1873-2747, Vol. 200, article id 110692Article in journal (Refereed)
    Abstract [en]

    Background: Lifestyle-related risk factors, such as obesity, physical inactivity, short sleep, smoking and alcohol use, have been associated with low hippocampal and total grey matter volumes (GMV). However, these risk factors have mostly been assessed as separate factors, leaving it unknown if variance explained by these factors is overlapping or additive. We investigated associations of five lifestyle-related factors separately and cumulatively with hippocampal and total GMV, pooled across eight European cohorts.

    Methods: We included 3838 participants aged 18–90 years from eight cohorts of the European Lifebrain consortium. Using individual person data, we performed cross-sectional meta-analyses on associations of presence of lifestyle-related risk factors separately (overweight/obesity, physical inactivity, short sleep, smoking, high alcohol use) as well as a cumulative unhealthy lifestyle score (counting the number of present lifestyle-related risk factors) with FreeSurfer-derived hippocampal volume and total GMV. Lifestyle-related risk factors were defined according to public health guidelines.

    Results: High alcohol use was associated with lower hippocampal volume (r = −0.10, p = 0.021), and overweight/obesity with lower total GMV (r = −0.09, p = 0.001). Other lifestyle-related risk factors were not significantly associated with hippocampal volume or GMV. The cumulative unhealthy lifestyle score was negatively associated with total GMV (r = −0.08, p = 0.001), but not hippocampal volume (r = −0.01, p = 0.625).

    Conclusions: This large pooled study confirmed the negative association of some lifestyle-related risk factors with hippocampal volume and GMV, although with small effect sizes. Lifestyle factors should not be seen in isolation as there is evidence that having multiple unhealthy lifestyle factors is associated with a linear reduction in overall brain volume.

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  • 38.
    Birnefeld, Johan
    et al.
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences.
    Petersson, Karl
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Anaesthesiology.
    Wåhlin, Anders
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Science and Technology, Centre for Biomedical Engineering and Physics (CMTF). Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Eklund, Anders
    Umeå University, Faculty of Science and Technology, Centre for Biomedical Engineering and Physics (CMTF). Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics.
    Birnefeld, Elin
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Anaesthesiology.
    Qvarlander, Sara
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Science and Technology, Centre for Biomedical Engineering and Physics (CMTF).
    Haney, Michael
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Anaesthesiology.
    Malm, Jan
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences.
    Zarrinkoob, Laleh
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Anaesthesiology.
    Cerebral blood flow assessed with phase-contrast magnetic resonance imaging during blood pressure changes with noradrenaline and labetalol: a trial in healthy volunteers 2023In: Anesthesiology, ISSN 0003-3022, E-ISSN 1528-1175Article in journal (Refereed)
    Abstract [en]

    Background: Adequate cerebral perfusion is central during general anesthesia. However, perfusion is not readily measured bedside. Clinicians currently rely mainly on MAP as a surrogate even though the relationship between blood pressure and cerebral blood flow is not well understood. The aim of this study was to apply phase contrast MRI to characterize blood flow responses in healthy volunteers to commonly used pharmacological agents that increase or decrease arterial blood pressure.

    Methods: Eighteen healthy volunteers aged 30-50 years were investigated with phase contrast MRI. Intraarterial blood pressure monitoring was used. First, intravenous noradrenaline was administered to a target MAP of 20% above baseline. After a wash-out period, intravenous labetalol was given to a target MAP of 15% below baseline. Cerebral blood flow was measured using phase contrast MRI and defined as the sum of flow in the internal carotid arteries and vertebral arteries. CO was defined as the flow in the ascending aorta.

    Baseline median cerebral blood flow was 772 ml/min (interquartile range, 674 to 871), and CO was 5,874 ml/min (5,199 to 6,355). The median dose of noradrenaline was 0.17 µg · kg−1 · h−1 (0.14 to 0.22). During noradrenaline infusion, cerebral blood flow decreased to 705 ml/min (606 to 748; P = 0.001), and CO decreased to 4,995 ml/min (4,705 to 5,635; P = 0.01). A median dose of labetalol was 120 mg (118 to 150). After labetalol boluses, cerebral blood flow was unchanged at 769 ml/min (734 to 900; P = 0.68). CO increased to 6,413 ml/min (6,056 to 7,464; P = 0.03).

    Conclusion: In healthy awake subjects, increasing MAP using intravenous noradrenaline decreased cerebral blood flow and CO. This data does not support inducing hypertension with noradrenaline to increase cerebral blood flow. Cerebral blood flow was unchanged when decreasing MAP using labetalol.

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  • 39.
    Birnefeld, Johan
    et al.
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences. Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience.
    Wåhlin, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Eklund, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Science and Technology, Centre for Biomedical Engineering and Physics (CMTF).
    Malm, Jan
    Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience.
    Cerebral arterial pulsatility is associated with features of small vessel disease in patients with acute stroke and TIA: a 4D flow MRI study2020In: Journal of Neurology, ISSN 0340-5354, E-ISSN 1432-1459, Vol. 267, no 3, p. 721-730Article in journal (Refereed)
    Abstract [en]

    Cerebral small vessel disease (SVD) is a major cause of stroke and cognitive impairment. However, the underlying mechanisms behind SVD are still poorly understood. High cerebral arterial pulsatility has been suggested as a possible cause of SVD. In population studies, arterial pulsatility has been linked to white matter hyperintensities (WMH), cerebral atrophy, and cognitive impairment, all features of SVD. In stroke, pulsatility data are scarce and contradictory. The aim of this study was to investigate the relationship between arterial pulsatility and SVD in stroke patients. With a cross-sectional design, 89 patients with acute ischemic stroke or TIA were examined with MRI. A neuropsychological assessment was performed 1 year later. Using 4D flow MRI, pulsatile indices (PI) were calculated for the internal carotid artery (ICA) and middle cerebral artery (M1, M3). Flow volume pulsatility (FVP), a measure corresponding to the cyclic expansion of the arterial tree, was calculated for the same locations. These parameters were assessed for associations with WMH volume, brain volume and cognitive function. ICA-FVP was associated with WMH volume (β = 1.67, 95% CI: [0.1, 3.24], p = 0.037). M1-PI and M1-FVP were associated with decreasing cognitive function (β = - 4.4, 95% CI: [- 7.7, - 1.1], p = 0.009 and β = - 13.15, 95% CI: [- 24.26, - 2.04], p = 0.02 respectively). In summary, this supports an association between arterial pulsatility and SVD in stroke patients, and provides a potential target for further research and preventative treatment. FVP may become a useful biomarker for assessing pulsatile stress with PCMRI and 4D flow MRI.

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  • 40.
    Björnfot, Cecilia
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Medicine, Department of Diagnostics and Intervention.
    Eklund, Anders
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Medicine, Department of Diagnostics and Intervention.
    Larsson, Jenny
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences.
    Hansson, William
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences.
    Birnefeld, Johan
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Diagnostics and Intervention.
    Qvarlander, Sara
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Medicine, Department of Diagnostics and Intervention.
    Koskinen, Lars-Owe D.
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences.
    Malm, Jan
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences.
    Wåhlin, Anders
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Science and Technology, Department of Applied Physics and Electronics. Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Umeå University, Faculty of Medicine, Department of Diagnostics and Intervention.
    Cerebral arterial stiffness is linked to white matter hyperintensities and perivascular spaces in older adults: a 4D flow MRI study2024In: Journal of Cerebral Blood Flow and Metabolism, ISSN 0271-678X, E-ISSN 1559-7016Article in journal (Refereed)
    Abstract [en]

    White matter hyperintensities (WMH), perivascular spaces (PVS) and lacunes are common MRI features of small vessel disease (SVD). However, no shared underlying pathological mechanism has been identified. We investigated whether SVD burden, in terms of WMH, PVS and lacune status, was related to changes in the cerebral arterial wall by applying global cerebral pulse wave velocity (gcPWV) measurements, a newly described marker of cerebral vascular stiffness. In a population-based cohort of 190 individuals, 66–85 years old, SVD features were estimated from T1-weighted and FLAIR images while gcPWV was estimated from 4D flow MRI data. Additionally, the gcPWV’s stability to variations in field-of-view was analyzed. The gcPWV was 10.82 (3.94) m/s and displayed a significant correlation to WMH and white matter PVS volume (r = 0.29, p < 0.001; r = 0.21, p = 0.004 respectively from nonparametric tests) that persisted after adjusting for age, blood pressure variables, body mass index, ApoB/A1 ratio, smoking as well as cerebral pulsatility index, a previously suggested early marker of SVD. The gcPWV displayed satisfactory stability to field-of-view variations. Our results suggest that SVD is accompanied by changes in the cerebral arterial wall that can be captured by considering the velocity of the pulse wave transmission through the cerebral arterial network.

  • 41.
    Björnfot, Cecilia
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Qvarlander, Sara
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Malm, Jan
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences.
    Eklund, Anders
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Wahlin, Anders
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Assessing cerebral arterial pulse wave velocity using 4D flow MRI2021In: Journal of Cerebral Blood Flow and Metabolism, ISSN 0271-678X, E-ISSN 1559-7016, Vol. 41, no 10, p. 2769-2777Article in journal (Refereed)
    Abstract [en]

    Intracranial arterial stiffening is a potential early marker of emerging cerebrovascular dysfunction and could be mechanistically involved in disease processes detrimental to brain function via several pathways. A prominent consequence of arterial wall stiffening is the increased velocity at which the systolic pressure pulse wave propagates through the vasculature. Previous non-invasive measurements of the pulse wave propagation have been performed on the aorta or extracranial arteries with results linking increased pulse wave velocity to brain pathology. However, there is a lack of intracranial “target-organ” measurements. Here we present a 4D flow MRI method to estimate pulse wave velocity in the intracranial vascular tree. The method utilizes the full detectable branching structure of the cerebral vascular tree in an optimization framework that exploits small temporal shifts that exists between waveforms sampled at varying depths in the vasculature. The method is shown to be stable in an internal consistency test, and of sufficient sensitivity to robustly detect age-related increases in intracranial pulse wave velocity.

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  • 42.
    Boen, Rune
    et al.
    Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
    Kaufmann, Tobias
    Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Germany; German Center for Mental Health (DZPG), partner site Tübingen, Tübingen, Germany.
    van der Meer, Dennis
    Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands.
    Frei, Oleksandr
    Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway.
    Agartz, Ingrid
    Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Clinical Research, Diakonhjemmet Hospital, Oslo, Norway; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden.
    Ames, David
    University of Melbourne Academic Unit for Psychiatry of Old Age, St George's Hospital, VIC, Kew, Australia; National Ageing Research Institute, VIC, Parkville, Australia.
    Andersson, Micael
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Armstrong, Nicola J.
    Department of Mathematics and Statistics, Curtin University, WA, Perth, Australia.
    Artiges, Eric
    Institut National de la Santé et de la Recherche Médicale U1299, École Normale Supérieure Paris-Saclay, Université Paris Saclay, Gif-sur-Yvette, France; Établissement public de santé (EPS) Barthélemy Durand, Etampes, France.
    Atkins, Joshua R.
    School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, NSW, Callaghan, Australia; Precision Medicine Research Program, Hunter Medical Research Institute, NSW, Newcastle, Australia; Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
    Bauer, Jochen
    University Clinic for Radiology, University of Münster, Münster, Germany.
    Benedetti, Francesco
    Psychiatry and Clinical Psychobiology Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy; Division of Neuroscience, Psychiatry and Clinical Psychobiology Unit, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy.
    Boomsma, Dorret I.
    Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
    Brodaty, Henry
    Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, NSW, Sydney, Australia.
    Brosch, Katharina
    Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany.
    Buckner, Randy L.
    Department of Psychology and Center for Brain Science, Harvard University, MA, Cambridge, United States; Department of Psychiatry, Massachusetts General Hospital, MA, Boston, United States.
    Cairns, Murray J.
    School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, NSW, Callaghan, Australia; Precision Medicine Research Program, Hunter Medical Research Institute, NSW, Newcastle, Australia.
    Calhoun, Vince
    Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University/Georgia Institute of Technology/Emory University, GA, Atlanta, United States.
    Caspers, Svenja
    Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
    Cichon, Sven
    Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Department of Biomedicine, University of Basel, Basel, Switzerland; University Hospital Basel, Institute of Medical Genetics and Pathology, Basel, Switzerland.
    Corvin, Aiden P.
    Department of Psychiatry, Trinity College Dublin, Dublin, Ireland.
    Crespo-Facorro, Benedicto
    Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/Centro superior de investigaciones científicas (CSIC), Sevilla, Spain; Centro de Investigación Biomédica en Red Salud Mental, Sevilla, Spain; Department of Psychiatry, University of Sevilla, Sevilla, Spain.
    Dannlowski, Udo
    Institute for Translational Psychiatry, University of Münster, Münster, Germany.
    David, Friederike S.
    Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany.
    de Geus, Eco J.C.
    Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
    de Zubicaray, Greig I.
    School of Psychology and Counselling, Queensland University of Technology, QLD, Brisbane, Australia.
    Desrivières, Sylvane
    Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
    Doherty, Joanne L.
    Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom; Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom.
    Donohoe, Gary
    School of Psychology and Center for Neuroimaging, Cognition and Genomics, University of Galway, Galway, Ireland.
    Ehrlich, Stefan
    Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.
    Eising, Else
    Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands.
    Espeseth, Thomas
    Department of Psychology, University of Oslo, Oslo, Norway; Department of Psychology, Oslo New University College, Oslo, Norway.
    Fisher, Simon E.
    Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands.
    Forstner, Andreas J.
    Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany.
    Fortaner-Uyà, Lidia
    Psychiatry and Clinical Psychobiology Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy; Division of Neuroscience, Psychiatry and Clinical Psychobiology Unit, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy.
    Frouin, Vincent
    Neurospin, Commissariat a l'Energie Atomique (CEA), Université Paris-Saclay, Gif-sur-Yvette, France.
    Fukunaga, Masaki
    Section of Brain Function Information, National Institute for Physiological Sciences, Okazaki, Japan.
    Ge, Tian
    Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, MA, Boston, United States; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, MA, Boston, United States.
    Glahn, David C.
    Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, MA, Boston, United States; Department of Psychiatry, Harvard Medical School, MA, Boston, United States.
    Goltermann, Janik
    Institute for Translational Psychiatry, University of Münster, Münster, Germany.
    Grabe, Hans J.
    Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
    Green, Melissa J.
    Discipline of Psychiatry and Mental Health, School of Clinical Medicine, University of New South Wales, NSW, Sydney, Australia; Neuroscience Research Australia, NSW, Sydney, Australia.
    Groenewold, Nynke A.
    Department of Psychiatry and Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa.
    Grotegerd, Dominik
    Institute for Translational Psychiatry, University of Münster, Münster, Germany.
    Grøntvedt, Gøril Rolfseng
    Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway.
    Hahn, Tim
    Institute for Translational Psychiatry, University of Münster, Münster, Germany.
    Hashimoto, Ryota
    Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Kodaira, Japan.
    Hehir-Kwa, Jayne Y.
    Princess Máxima Center for Pediatric Oncology, Utrecht, Netherlands.
    Henskens, Frans A.
    School of Medicine and Public Health, University of Newcastle, NSW, Newcastle, Australia; Priority Research Centre for Health Behaviour, University of Newcastle, NSW, Newcastle, Australia.
    Holmes, Avram J.
    Department of Psychiatry, Rutgers University, NJ, New Brunswick, United States; Brain Health Institute, Rutgers University, NJ, Piscataway, United States.
    Håberg, Asta K.
    Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Radiology and Nuclear Medicine, St. Olav's Hospital, Trondheim, Norway.
    Haavik, Jan
    Department of Biomedicine, University of Bergen, Bergen, Norway; Division of Psychiatry, Haukeland University Hospital, Bergen, Norway.
    Jacquemont, Sebastien
    Sainte Justine Hospital Research Center, QC, Montreal, Canada; Department of Pediatrics, University of Montreal, QC, Montreal, Canada.
    Jansen, Andreas
    Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany; Core-Facility Brainimaging and Department of Psychiatry, Faculty of Medicine, Philipps-University Marburg, Marburg, Germany.
    Jockwitz, Christiane
    Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
    Jönsson, Erik G.
    Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden.
    Kikuchi, Masataka
    Department of Genome Informatics, Graduate School of Medicine, Osaka University, Osaka, Japan; Department of Computational Biology and Medical Sciences, Graduate School of Frontier Science, The University of Tokyo, Chiba, Japan.
    Kircher, Tilo
    Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany.
    Kumar, Kuldeep
    Sainte Justine Hospital Research Center, QC, Montreal, Canada.
    Le Hellard, Stephanie
    Norwegian Centre for Mental Disorders Research, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway.
    Leu, Costin
    Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Department of Neurology, McGovern Medical School, UTHealth Houston, TX, Houston, United States.
    Linden, David E.
    Neuroscience and Mental Health Innovation Institute, Cardiff University, Cardiff, United Kingdom; School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands.
    Liu, Jingyu
    Department of Computer Science and Center for Translational Research in Neuroimaging and Data Science, Georgia State University, GA, Atlanta, United States.
    Loughnan, Robert
    Department of Cognitive Science and Population Neuroscience and Genetics Lab, University of California San Diego, CA, La Jolla, United States.
    Mather, Karen A.
    Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, NSW, Sydney, Australia.
    McMahon, Katie L.
    School of Clinical Sciences, Queensland University of Technology, QLD, Brisbane, Australia.
    McRae, Allan F.
    Institute for Molecular Bioscience, The University of Queensland, QLD, Brisbane, Australia.
    Medland, Sarah E.
    Psychiatric Genetics, Queensland Institute of Medical Research (QIMR) Berghofer Medical Research Institute, QLD, Brisbane, Australia; University of Queensland, QLD, Brisbane, Australia; Queensland University of Technology, QLD, Brisbane, Australia.
    Meinert, Susanne
    Institute for Translational Psychiatry, University of Münster, Münster, Germany; Institute for Translational Neuroscience, University of Münster, Münster, Germany.
    Moreau, Clara A.
    Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, CA, Marina del Rey, United States.
    Morris, Derek W.
    Centre for Neuroimaging, Cognition and Genomics, School of Biological and Chemical Sciences, University of Galway, Galway, Ireland.
    Mowry, Bryan J.
    Queensland Brain Institute and Queensland Centre for Mental Health Research, University of Queensland, QLD, Brisbane, Australia.
    Mühleisen, Thomas W.
    Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Department of Biomedicine, University of Basel, Basel, Switzerland.
    Nenadić, Igor
    Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany.
    Nöthen, Markus M.
    Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Ophoff, Roel A.
    Department of Psychiatry, Erasmus University Medical Center, Rotterdam, Netherlands; Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, University of California Los Angeles, CA, Los Angeles, United States.
    Owen, Michael J.
    Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom; Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom.
    Pantelis, Christos
    Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Carlton South, Victoria, Australia; Western Centre for Health Research and Education, Sunshine Hospital, VIC, St Albans, Australia.
    Paolini, Marco
    Psychiatry and Clinical Psychobiology Unit, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele Scientific Institute, Milan, Italy; Division of Neuroscience, Psychiatry and Clinical Psychobiology Unit, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy.
    Paus, Tomas
    Departments of Psychiatry and Neuroscience, Faculty of Medicine and Sainte Justine Hospital Research Center, University of Montreal, QC, Montreal, Canada; Departments of Psychiatry and Psychology, University of Toronto, ON, Toronto, Canada.
    Pausova, Zdenka
    The Hospital for Sick Children, ON, Toronto, Canada; Department of Physiology, University of Toronto, ON, Toronto, Canada.
    Persson, Karin
    Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway; Norwegian National Centre for Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway.
    Quidé, Yann
    Neuroscience Research Australia, NSW, Sydney, Australia; School of Psychology, University of New South Wales, NSW, Sydney, Australia.
    Marques, Tiago Reis
    Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
    Sachdev, Perminder S.
    Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, NSW, Sydney, Australia; Neuropsychiatric Institute, Prince of Wales Hospital, NSW, Sydney, Australia.
    Sando, Sigrid B.
    Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway.
    Schall, Ulrich
    Hunter Medical Research Institute, NSW, Newcastle, Australia.
    Scott, Rodney J.
    School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, NSW, Callaghan, Australia; Hunter Medical Research Institute, NSW, Newcastle, Australia; Division of Molecular Medicine, New South Wales Health Pathology, NSW, Newcastle, Australia.
    Selbæk, Geir
    Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway; Norwegian National Centre for Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway; Faculty of Medicine, University of Oslo, Oslo, Norway.
    Shumskaya, Elena
    Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands; Department of Human Genetics, Radboud University Medical Center, Nijmegen, Netherlands.
    Silva, Ana I.
    Neuroscience and Mental Health Innovation Institute, Cardiff University, Cardiff, United Kingdom.
    Sisodiya, Sanjay M.
    Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Chalfont Centre for Epilepsy, Chalfont St Peter, United Kingdom.
    Stein, Frederike
    Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany.
    Stein, Dan J.
    SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa.
    Straube, Benjamin
    Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany.
    Streit, Fabian
    Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.
    Strike, Lachlan T.
    Psychiatric Genetics, Queensland Institute of Medical Research (QIMR) Berghofer Medical Research Institute, QLD, Brisbane, Australia; School of Psychology and Counselling, Faculty of Health, Queensland University of Technology, Brisbane, Australia.
    Teumer, Alexander
    Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany; Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; German Centre for Cardiovascular Research, Greifswald, Germany.
    Teutenberg, Lea
    Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany.
    Thalamuthu, Anbupalam
    Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, NSW, Sydney, Australia.
    Tooney, Paul A.
    School of Biomedical Sciences and Pharmacy, College of Medicine, Health and Wellbeing, University of Newcastle, NSW, Callaghan, Australia; Hunter Medical Research Institute, NSW, Newcastle, Australia.
    Tordesillas-Gutierrez, Diana
    Instituto de Física de Cantabria UC-CSIC, Santander, Spain; Department of Radiology, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute, Instituto de Investigación Sanitaria Valdecilla, Santander, Spain.
    Trollor, Julian N.
    Department of Developmental Disability Neuropsychiatry and Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, NSW, Sydney, Australia.
    van ’t Ent, Dennis
    Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
    van den Bree, Marianne B.M.
    Institute of Psychological Medicine and Clinical Neurosciences and Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom; Institute for Translational Neuroscience, University of Münster, Münster, Germany.
    van Haren, Neeltje E.M.
    Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Rotterdam, Netherlands; Department of Psychiatry, University Medical Centre Utrecht, Utrecht, Netherlands.
    Vázquez-Bourgon, Javier
    Centro de Investigación Biomédica en Red Salud Mental, Sevilla, Spain; Department of Psychiatry, University Hospital Maqués de Valdecilla, Instituto de Investigación Sanitaria Valdecilla, Santander, Spain; Departamento de Medicina y Psiquiatría, Universidad de Cantabria, Santander, Spain.
    Völzke, Henry
    German Centre for Cardiovascular Research, Greifswald, Germany; Greifswald University Hospital, Greifswald, Germany.
    Wen, Wei
    Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, NSW, Sydney, Australia.
    Wittfeld, Katharina
    Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
    Ching, Christopher R.K.
    Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, CA, Marina del Rey, United States.
    Westlye, Lars T.
    Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway.
    Thompson, Paul M.
    Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, CA, Marina del Rey, United States.
    Bearden, Carrie E.
    Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, University of California Los Angeles, CA, Los Angeles, United States.
    Selmer, Kaja K.
    Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital and the University of Oslo, Oslo, Norway.
    Alnæs, Dag
    Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Kristiania University College, Oslo, Norway.
    Andreassen, Ole A.
    Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway.
    Sønderby, Ida E.
    Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway.
    Beyond the global brain differences: intraindividual variability differences in 1q21.1 distal and 15q11.2 bp1-bp2 deletion carriers2024In: Biological Psychiatry, ISSN 0006-3223, E-ISSN 1873-2402, Vol. 95, no 2, p. 147-160Article in journal (Refereed)
    Abstract [en]

    Background: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure.

    Methods: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference.

    Results: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness.

    Conclusions: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.

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  • 43.
    Boraxbekk, Carl-Johan
    Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Danish Research Center for Magnetic Research (DRCMR), Centre forFunctional and Diagnostic Imaging and Research, Copenhagen Univer-sity Hospital Hvidovre, Hvidovre, Denmark.
    Non-invasive brain stimulation and neuro-enhancement in aging2018In: Clinical Neurophysiology, ISSN 1388-2457, E-ISSN 1872-8952, Vol. 9, p. 464-465Article in journal (Refereed)
  • 44.
    Boraxbekk, Carl-Johan
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Ames, David
    Kochan, Nicole
    Lee, Teresa
    Thalamuthu, Anbupalam
    Wen, Wei
    Armstrong, Nicola
    Kwok, John
    Schofield, Peter
    Reppermund, Simone
    Wright, Margaret
    Trollor, Julian
    Brodaty, Henry
    Sachdev, Perminder
    Mather, Karen
    Investigating the influence of KIBRA and CLSTN2 genetic polymorphisms on cross-sectional and longitudinal measures of memory performance and hippocampal volume in older individuals2015In: Neuropsychologia, ISSN 0028-3932, E-ISSN 1873-3514, Vol. 78, p. 10-17Article in journal (Refereed)
    Abstract [en]

    The variability of episodic memory decline and hippocampal atrophy observed with increasing age may partly be explained by genetic factors. KIBRA (kidney and brain expressed protein) and CLSTN2 (calsyntenin 2) are two candidate genes previously linked to episodic memory performance and volume of the hippocampus, a key memory structure. However, whether polymorphisms in these two genes also influence age-related longitudinal memory decline and hippocampal atrophy is still unknown. Using data from two independent cohorts, the Sydney Memory and Ageing Study and the Older Australian Twins Study, we investigated whether the KIBRA and CLSTN2 genetic polymorphisms (rs17070145 and rs6439886) are associated with episodic memory performance and hippocampal volume in older adults (65–90 years at baseline). We were able to examine these polymorphisms in relation to memory and hippocampal volume using cross-sectional data and, more importantly, also using longitudinal data (2 years between testing occasions). Overall we did not find support for an association of KIBRA either alone or in combination with CLSTN2 with memory performance or hippocampal volume, nor did variation in these genes influence longitudinal memory decline or hippocampal atrophy in two cohorts of older adults.

  • 45.
    Boraxbekk, Carl-Johan
    et al.
    Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Hagkvist, Filip
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Lindner, Philip
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Department of Clinical Neuroscience, Karolinska Institutet; Department of Psychology, Stockholm University.
    Motor and mental training in older people: transfer, interference, and associated functional neural responses2016In: Neuropsychologia, ISSN 0028-3932, E-ISSN 1873-3514, Vol. 89, p. 371-377Article in journal (Refereed)
    Abstract [en]

    Learning new motor skills may become more difficult with advanced age. In the present study, we randomized 56 older individuals, including 30 women (mean age 70.6 years), to 6 weeks of motor training, mental (motor imagery) training, or a combination of motor and mental training of a finger tapping sequence. Performance improvements and post-training functional magnetic resonance imaging (fMRI) were used to investigate performance gains and associated underlying neural processes. Motor-only training and a combination of motor and mental training improved performance in the trained task more than mental-only training. The fMRI data showed that motor training was associated with a representation in the premotor cortex and mental training with a representation in the secondary visual cortex. Combining motor and mental training resulted in both premotor and visual cortex representations. During fMRI scanning, reduced performance was observed in the combined motor and mental training group, possibly indicating interference between the two training methods. We concluded that motor and motor imagery training in older individuals is associated with different functional brain responses. Furthermore, adding mental training to motor training did not result in additional performance gains compared to motor-only training and combining training methods may result in interference between representations, reducing performance.

  • 46.
    Boraxbekk, Carl-Johan
    et al.
    Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Salami, Alireza
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Aging Research Center (ARC), Karolinska Institute, Stockholm, Sweden.
    Wåhlin, Anders
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB), Physiology. Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology.
    Physical activity over a decade modifies age-related decline in perfusion, gray matter volume, and functional connectivity of the posterior default mode network: a multimodal approach2016In: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 131, p. 133-141Article in journal (Refereed)
    Abstract [en]

    One step toward healthy brain aging may be to entertain a physically active lifestyle. Studies investigating physical activity effects on brain integrity have, however, mainly been based on single brain markers, and few used a multimodal imaging approach. In the present study, we used cohort data from the Betula study to examine the relationships between scores reflecting current and accumulated physical activity and brain health. More specifically, we first examined if physical activity scores modulated negative effects of age on seven resting state networks previously identified by Salami, Pudas, and Nyberg (2014). The results revealed that one of the most age-sensitive RSN was positively altered by physical activity, namely, the posterior default-mode network involving the posterior cingulate cortex (PCC). Second, within this physical activity-sensitive RSN, we further analyzed the association between physical activity and gray matter (GM) volumes, white matter integrity, and cerebral perfusion using linear regression models. Regions within the identified DMN displayed larger GM volumes and stronger perfusion in relation to both current and 10-years accumulated scores of physical activity. No associations of physical activity and white matter integrity were observed. Collectively, our findings demonstrate strengthened PCC–cortical connectivity within the DMN, larger PCC GM volume, and higher PCC perfusion as a function of physical activity. In turn, these findings may provide insights into the mechanisms of how long-term regular exercise can contribute to healthy brain aging.

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  • 47.
    Boraxbekk, Carl-Johan
    et al.
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Social Sciences, Centre for Population Studies (CPS).
    Stomby, Andreas
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Ryberg, Mats
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Lindahl, Bernt
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine.
    Larsson, Christel
    Umeå University, Faculty of Social Sciences, Department of Food and Nutrition. Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Göteborgs Universitet.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Olsson, Tommy
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Diet-Induced Weight Loss alters Functional Brain Responses during an Episodic Memory Task2015In: Obesity Facts, ISSN 1662-4025, E-ISSN 1662-4033, Vol. 8, p. 261-272Article in journal (Refereed)
    Abstract [en]

    Objective: It has been suggested that overweight is negatively associated with cognitive functions. The aim of this study was to investigate whether a reduction in body weight by dietary interventions could improve episodic memory performance and alter associated functional brain responses in overweight and obese women. Methods: 20 overweight postmenopausal women were randomized to either a modified paleolithic diet or a standard diet adhering to the Nordic Nutrition Recommendations for 6 months. We used functional magnetic resonance imaging to examine brain function during an episodic memory task as well as anthropometric and biochemical data before and after the interventions. Results: Episodic memory performance improved significantly (p = 0.010) after the dietary interventions. Concomitantly, brain activity increased in the anterior part of the right hippocampus during memory encoding, without differences between diets. This was associated with decreased levels of plasma free fatty acids (FFA). Brain activity increased in pre-frontal cortex and superior/middle temporal gyri. The magnitude of increase correlated with waist circumference reduction. During episodic retrieval, brain activity decreased in inferior and middle frontal gyri, and increased in middle/superior temporal gyri. Conclusions: Diet-induced weight loss, associated with decreased levels of plasma FFA, improves episodic memory linked to increased hippocampal activity.

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  • 48.
    Bäcklund, Christian
    et al.
    Department of Health, Education and Technology, Luleå University of Technology, Laboratorievägen 14, Luleå, Sweden.
    Elbe, Pia
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Department of Health, Education and Technology, Luleå University of Technology, Laboratorievägen 14, Luleå, Sweden.
    Gavelin, Hanna M.
    Umeå University, Faculty of Social Sciences, Department of Psychology.
    Sörman, Daniel Eriksson
    Department of Health, Education and Technology, Luleå University of Technology, Laboratorievägen 14, Luleå, Sweden.
    Ljungberg, Jessica K.
    Department of Health, Education and Technology, Luleå University of Technology, Laboratorievägen 14, Luleå, Sweden.
    Gaming motivations and gaming disorder symptoms: A systematic review and meta-analysis2022In: Journal of Behavioral Addictions, ISSN 2062-5871, E-ISSN 2063-5303, Vol. 11, no 3, p. 667-688Article, review/survey (Refereed)
    Abstract [en]

    Background and aims: The present systematic review and meta-analysis aimed to synthesize the available literature on the relationship between gaming motivations and gaming disorder symptoms. Specifically, to (1) explore what gaming motivation questionnaires and classifications are used in studies on gaming disorder symptoms and (2) investigate the relationship between motivational factors and symptoms of gaming disorder.

    Method: An electronic database search was conducted via EBSCO (MEDLINE and PsycINFO) and the Web of Science Core Collection. All studies using validated measurements on gaming disorder symptoms and gaming motivations and available correlation coefficients of the relationship between gaming disorder and gaming motivations were included. The meta-analyses were conducted using a random-effects model.

    Results: In total, 49 studies (k = 58 independent sub-samples), including 51,440 participants, out of which 46 studies (k = 55 sub-samples, n = 49,192 participants) provided data for the meta-analysis. The synthesis identified fourteen different gaming motivation instruments, seven unique motivation models, and 26 motivational factors. The meta-analysis showed statistically significant associations between gaming disorder symptoms and 23 out of 26 motivational factors, with the majority of the pooled mean effect sizes ranging from small to moderate. Moreover, large heterogeneity was observed, and the calculated prediction intervals indicated substantial variation in effects across populations and settings. Motivations related to emotional escape were robustly associated with gaming disorder symptoms.

    Discussion and conclusions: The present meta-analysis reinforces the importance of motivational factors in understanding problematic gaming behavior. The analysis showed significant heterogeneity in most outcomes, warranting further investigation.

    Registration detail: PROSPERO (CRD42020220050).

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  • 49.
    Bäckman, Lars
    et al.
    Aging Research Center, Karolinska Institutet, Gävlegatan 16, SE-113 30 Stockholm, Sweden.
    Karlsson, Sari
    Aging Research Center, Karolinska Institutet, Gävlegatan 16, SE-113 30 Stockholm, Sweden.
    Fischer, Håkan
    Aging Research Center, Karolinska Institutet, Gävlegatan 16, SE-113 30 Stockholm, Sweden.
    Karlsson, Per
    Department of Clinical Neuroscience, Psychiatry Section, Karolinska Institutet, Stockholm, Sweden.
    Brehmer, Yvonne
    Aging Research Center, Karolinska Institutet, Gävlegatan 16, SE-113 30 Stockholm, Sweden.
    Rieckmann, Anna
    Aging Research Center, Karolinska Institutet, Gävlegatan 16, SE-113 30 Stockholm, Sweden.
    Macdonald, Stuart WS
    Aging Research Center, Karolinska Institutet, Gävlegatan 16, SE-113 30 Stockholm, Sweden; Department of Psychology, University of Victoria, Canada .
    Farde, Lars
    Department of Clinical Neuroscience, Psychiatry Section, Karolinska Institutet, Stockholm, Sweden.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB).
    Dopamine D(1) receptors and age differences in brain activation during working memory2011In: Neurobiology of Aging, ISSN 0197-4580, E-ISSN 1558-1497, Vol. 32, no 10, p. 1849-1856Article in journal (Refereed)
    Abstract [en]

    In an fMRI study, 20 younger and 20 healthy older adults were scanned while performing a spatial working-memory task under two levels of load. On a separate occasion, the same subjects underwent PET measurements using the radioligand [(11)C] SCH23390 to determine dopamine D(1) receptor binding potential (BP) in caudate nucleus and dorsolateral prefrontal cortex (DLPFC). The fMRI study revealed a significant load modulation of brain activity (higher load>lower load) in frontal and parietal regions for younger, but not older, adults. The PET measurements showed marked age-related reductions of D(1) BP in caudate and DLPFC. Statistical control of caudate and DLPFC D(1) binding eliminated the age-related reduction in load-dependent BOLD signal in left frontal cortex, and attenuated greatly the reduction in right frontal and left parietal cortex. These findings suggest that age-related alterations in dopaminergic neurotransmission may contribute to underrecruitment of task-relevant brain regions during working-memory performance in old age.

  • 50.
    Bäckström, David C
    et al.
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences. DeDepartment of Neurology, Yale University, New Haven, CT, USA.
    Granåsen, Gabriel
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health.
    Jakobson Mo, Susanna
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Riklund, Katrine
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Diagnostic Radiology. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Trupp, Miles
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences.
    Zetterberg, Henrik
    Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease and UCL Queen Square Institute of Neurology, London, UK; UK Dementia Research Institute at UCL, London, UK.
    Blennow, Kaj
    Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.
    Forsgren, Lars
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Neurosciences.
    Eriksson Domellöf, Magdalena
    Umeå University, Faculty of Social Sciences, Department of Psychology.
    Prediction and early biomarkers of cognitive decline in Parkinson disease and atypical parkinsonism: a population-based study2022In: Brain Communications, E-ISSN 2632-1297, Vol. 4, no 2Article in journal (Refereed)
    Abstract [en]

    The progression of cognitive decline is heterogeneous in the three most common idiopathic parkinsonian diseases: Parkinson disease, multiple system atrophy and progressive supranuclear palsy. The causes for this heterogeneity are not fully understood, and there are no validated biomarkers that can accurately identify patients who will develop dementia and when. In this population-based, prospective study, comprehensive neuropsychological testing was performed repeatedly in new-onset, idiopathic parkinsonism. Dementia was diagnosed until 10 years and participants (N = 210) were deeply phenotyped by multimodal clinical, biochemical, genetic and brain imaging measures. At baseline, before the start of dopaminergic treatment, mild cognitive impairment was prevalent in 43.4% of the patients with Parkinson disease, 23.1% of the patients with multiple system atrophy and 77.8% of the patients with progressive supranuclear palsy. Longitudinally, all three diseases had a higher incidence of cognitive decline compared with healthy controls, but the types and severity of cognitive dysfunctions differed. In Parkinson disease, psychomotor speed and attention showed signs of improvement after dopaminergic treatment, while no such improvement was seen in other diseases. The 10-year cumulative probability of dementia was 54% in Parkinson disease and 71% in progressive supranuclear palsy, while there were no cases of dementia in multiple system atrophy. An easy-to-use, multivariable model that predicts the risk of dementia in Parkinson disease within 10 years with high accuracy (area under the curve: 0.86, P < 0.001) was developed. The optimized model adds CSF biomarkers to four easily measurable clinical features at baseline (mild cognitive impairment, olfactory function, motor disease severity and age). The model demonstrates a highly variable but predictable risk of dementia in Parkinson disease, e.g. a 9% risk within 10 years in a patient with normal cognition and CSF amyloid-β42 in the highest tertile, compared with an 85% risk in a patient with mild cognitive impairment and CSF amyloid-β42 in the lowest tertile. Only small or no associations with cognitive decline were found for factors that could be easily modifiable (such as thyroid dysfunction). Risk factors for cognitive decline in multiple system atrophy and progressive supranuclear palsy included signs of systemic inflammation and eye movement abnormalities. The predictive model has high accuracy in Parkinson disease and might be used for the selection of patients into clinical trials or as an aid to improve the prevention of dementia. 

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